Genpact has launched the Genpact AI Gigafactory, an innovative accelerator aimed at scaling AI solutions from pilot projects to enterprise-wide deployment. This initiative seeks to address the increasing demand for AI adoption while ensuring robust governance and ethical practices.

“The benefits of AI are clear, but most businesses struggle with how to implement it at scale,” said Sanjeev Vohra, chief technology and innovation officer at Genpact. “A multi-disciplinary approach is essential to drive transformative impact—one that combines deep industry knowledge, expertise in data, technology, and processes, along with highly specialized talent.”

A recent study by Genpact and HFS Research revealed that only 5% of organisations have achieved full AI maturity. 

Genpact’s proprietary Agentic Solutions and pre-built AI models accelerate efficiency by enabling repeatability and speed-to-value for scaling AI solutions. Leveraging cross-functional teams with deep expertise in data engineering, industry processes, and technology integration, the Gigafactory is expected to create a talent pool of over 25,000 AI builders.

Emphasising ethical AI design, the Gigafactory employs tools and a ‘humans-in-the-loop’ approach to ensure the safe and ethical use of AI and data.

Vishal Gupta, Partner at Everest Group, highlighted the significance of this initiative, stating, “A key challenge in this journey is access to cross-functional, AI-ready talent. Genpact’s AI Gigafactory solution tackles this challenge by collaborating with technology partners and building a pool of highly skilled professionals through comprehensive training programs. This approach enables faster deployment of AI-ready professionals and accelerates value realization for enterprise clients.”

The Gigafactory is supported by strategic partnerships with ecosystem players such as Databricks, enabling enterprises to integrate AI solutions seamlessly. “We see Genpact’s AI Gigafactory as a critical solution in helping companies scale their AI projects,” said Sabina Shaikh, VP, Global Systems Integrators at Databricks.

Genpact recently also promoted Sreekanth Menon to the position of senior vice president of Global AI Practice and Innovation. In his new role, Menon will spearhead AI innovation and oversee the execution of the GenpactNEXT strategy. He will operate from the company’s Bengaluru office.

Genpact has promoted Sreekanth Menon to the position of senior vice president of Global AI Practice and Innovation. In his new role, Menon will spearhead AI innovation and oversee the execution of the GenpactNEXT strategy. He will operate from the company’s Bengaluru office.

Commenting on his appointment, Menon expressed enthusiasm about his new responsibilities. “The AI landscape is evolving rapidly, and I’m thrilled to help drive our GenpactNEXT strategy—pioneering innovation, delivering client impact, and shaping the future of AI together. This is an exciting chapter for Genpact, and I’m honored to play a part in its success,” he stated in a LinkedIn post.

Menon has been associated with Genpact for 15 years. In his previous role as vice president and global leader for AI/ML services, he led a global team of over 200 cross-functional experts within Genpact Global Analytics. During his tenure, he successfully scaled the team eightfold within five years. Menon holds degrees from XLRI Jamshedpur and Bangalore University.

This promotion comes as part of Genpact’s broader leadership reshuffle. Last year, the company appointed Piyush Mehta as India country manager, adding to his role as chief human resource officer. 

Additionally, after the retirement of NV ‘Tiger’ Tyagarajan as president and CEO in February 2024, Balkrishan ‘BK’ Kalra was named his successor. Kalra, a Genpact veteran since 1999, previously served as the global business leader for financial services and consumer and healthcare segments.

Further strengthening its leadership team, Genpact also appointed Vidya Rao as chief technology and transformation officer and Vipin Gairola as the Global Operating Officer.

Genpact has appointed Jinsook Han as its chief strategy and corporate development officer, effective immediately. Han will report directly to President and CEO Balkrishan “BK” Kalra and will be responsible for the company’s strategy and investments, including ventures and acquisitions.

Working as a cloud, engineering, data & AI partner at PwC, Han was instrumental in shaping and advising large transformations for clients. 

Prior to PwC, she was the chief strategy officer of the Applied Intelligence Business at Accenture.  In this role, she refreshed growth strategies, incubated new businesses, managed R&D funding, expanded strategic partnerships and increased acquisitions. Han also held executive strategy and technology roles at AIG and McKinsey & Company.

“Together, we will focus on identifying and executing on high impact opportunities, elevating our capabilities, and expanding our partnership ecosystem. I look forward to bringing my expertise to help advance Genpact’s growth and to truly drive transformation not only within the company but across the offerings and solutions we provide to our clients,” said Han, announcing her excitement for the new role. 

“Jinsook has that rare profile that combines a deep understanding of how data, analytics and AI will transform industries, with strong M&A experience that drives shareholder value and a keen ability to bring teams together towards a common goal,” said Kalra. “I am delighted to welcome Jinsook to Genpact where she will guide our leadership team as we continue to drive superior value for our clients, harnessing the combined power of Genpact’s industry knowledge, data, and artificial intelligence.”

Genpact has been expanding its leadership roles for a while now. In August, the company named Sanjeev Vohra as its first chief technology & innovation officer. In April, it appointed its chief human resources officer (CHRO), Piyush Mehta, as the Country Manager for India, signaling the company’s deepening commitment to innovation, growth, and talent development in the region. 

The Association of Data Scientists (ADaSci) started the fifth batch of Genpact’s SkyDive Global Campus Academy last month. Five batches of the SkyDive program have been successfully completed so far with four in collaboration with ADaSci. This nine-week persona-driven experiential learning program aims to bridge the gap between academic learning and corporate demands, equipping fresh graduates with essential skills for today’s dynamic business environment.

Genpact is a global professional services firm that drives digital transformation for enterprises. Focusing on Data, Analytics, and AI, Genpact is on a strategic journey to become an AI-first company, revolutionising business operations and innovation. The SkyDive program reflects Genpact’s dedication to preparing the workforce for the evolving landscape of digital transformation.

This year’s SkyDive edition introduces three specialisation tracks: Advanced Analytics & Generative AI, Data Visualization, BI & Reporting, and Data Engineering.

With a focus on generative AI, Genpact is committed to nurturing talent poised to drive innovation in this transformative technology. The SkyDive Global Campus Academy reflects this commitment, preparing graduates to excel in an AI-driven future.

“The SkyDive Global Campus Academy has been instrumental in shaping the future leaders of our organisation. As we continue our journey towards becoming an AI-first company, the inclusion of Generative AI as a specialisation track in this year’s program underscores our commitment to staying ahead of the curve. We believe that equipping our graduates with these advanced skills will not only benefit Genpact but also drive innovation and transformation across the industries we serve,” said Sreekanth Menon, Vice President and Global AI Leader at Genpact

“The SkyDive program represents a crucial step in bridging the gap between academic training and industry demands. At ADaSci, we are proud to support Genpact’s vision by contributing our expertise in advanced analytics and AI. Our collaboration ensures that SkyDive delivers a rigorous and relevant training experience, equipping fresh graduates with the skills necessary to excel in today’s fast-paced business environment. This partnership is a testament to our commitment to shaping the future of talent development,” said Bhasker Gupta, President, ADaSci.

Program Highlights

The SkyDive Global Campus Academy is a 9-week program designed to provide a comprehensive learning experience:

• Baseline Training (Weeks 1-4): Covers foundational technical skills and business acumen.
• Specialisation Tracks (Weeks 5-8): Offers deep dives into Advanced Analytics & Generative AI, Data Visualization, BI & Reporting, or Data Engineering.
• Capstone Projects (Week 9): Participants tackle real-world challenges and present their projects to industry experts.

What to Expect?

Graduates will acquire mastery in their chosen specialisation, gain practical experience through hands-on labs and projects, and develop a deep understanding of industry trends and best practices.

The program also emphasises the enhancement of soft skills, including communication and leadership, while providing valuable networking opportunities with peers, mentors, and industry leaders.

“Generative AI is more than just a tool; it’s a game-changer. As businesses increasingly look to AI to drive efficiency and creativity, we need to ensure that our workforce is not only familiar with these technologies but proficient in leveraging them to create value. By including a specialisation track in Generative AI, we are empowering our graduates with the knowledge and skills they need to lead the next generation of AI-driven innovation,” said Sreekanth Menon.

The SkyDive Global Campus Academy has consistently bridged the gap between academia and industry, with over 500 graduates making significant contributions to Genpact and beyond.

With the massive volume of AI solutions at play, separating actual impactful work from all the hype surrounding AI becomes crucial. “There’s just so much noise out there. And there’s so much innovation. It’s hard to tell fact from fiction,” said Edmund DeLussey, global enterprise leader at Genpact, during a keynote at AIM’s MachineCon Summit in New York. 

Five-Principle Approach

Genpact emphasises a strategic approach grounded in five fundamental principles to succeed with generative AI. 

The first is identifying the right projects by analysing vast amounts of data to uncover trends and evaluate outcomes. The company recommends creating a centre of excellence (CoE) to develop expertise, assess infrastructure needs, and select promising use cases. This approach has enabled Genpact to drive innovative solutions internally, as well as for its clients.

The second principle is embedding AI into processes. A seamless integration into existing workflows empowers decision-makers with real-time insights. A case in point is Genpact’s work with a media conglomerate, where they used GenAI to create a superintelligent assistant, boosting customer satisfaction and sales by providing real-time recommendations.

Prioritising data governance and responsible AI is the third principle. Establishing a strong data foundation and ethical practices enables fair and trustworthy AI solutions. Genpact’s responsible AI framework, illustrated by their collaboration with a global bank, demonstrates how sound governance can streamline processes and enhance transparency.

>> Read insights from 550 senior leaders at the forefront of the AI revolution

The fourth principle involves building a robust technical architecture, which includes scalable infrastructure and effective model management. Genpact’s work with a leading brewing company shows how a strong data platform can improve accuracy, productivity, and decision-making, driving digital transformation.

Finally, enabling a scalable operating model is crucial. Standardising processes and developing adaptable teams allow organisations to respond quickly to changing needs. Genpact’s work with a global retailer, which significantly reduced supplier disputes through enhanced data processes, highlights the effectiveness of this approach.

AI Across Sectors 

Besides discussing the length and breadth of AI applications across industries like life sciences, consumer goods, and automobiles, DeLussey also touched upon the challenge of bringing AI to a person, or rather, how AI would be accessible to people. 

“One of the things we need to be thinking about is how do we bring AI to a person? How do we do what Microsoft is trying to do with their Copilot that they just released in beta…? How do you use a tool like that to help with busy areas of finance [and other business functions]?” said DeLussey. 

AI for People

While talking about bringing AI to employees and customers, DeLussey mentioned that one of Genpact’s partners, in collaboration with Salesforce, was developing an AI service management platform for an auto manufacturer. 

The AI system aggregated data on individual car services, warranties and other relevant information. This helped service technicians quickly identify the correct repairs and avoid the hassle of a customer repeatedly talking about the vehicle’s service history or searching the web for those details. 

“This [AI consolidating and summarising data] is an area we’re really excited about. We think there’s going to be a ton of innovation in this space, and it’s going to enable many people to do better work,” said DeLussey. He believes the technology will not only boost productivity but also increase revenues. 

AI in Healthcare

DeLussey also shed light on AI in drug discovery and its advancement over the years. “In 2015, there was exactly one AI-designed drug in clinical trials, but by the end of 2023, there were 67. As of now, there’s not a single drug that has actually made it out into the market yet, but it’s only a matter of time,” he said. 

The FDA has approved approximately 700 models and developed new methods to streamline the process. With advancements in protein folding, such as Google DeepMind’s AlphaFold 3 which delivers a 50% prediction accuracy, AI models assisting drug discoveries will only accelerate. 

Interestingly, DeLussey brought sector-focused solutions that AI companies are working on to attention. In healthcare verticals, big-tech companies, such as Microsoft and Google, are building language models to assist in the medical field. Many startups, too, are working in this space. 

DeLussey also discussed how consumer product companies use AI to create new food items. For example, he emphasised how Unilever has developed zero-salt alternatives using different AI combinations and released a vegan version of Hellmann’s mayonnaise that tastes like regular mayonnaise. 

Moreover, consumer product companies have also been using AI to minimise waste and improve sustainability. DeLussey gave the example of chocolate manufacturer Mars, which is using AI to improve its sustainability strategies, like using recyclable paper wrappers instead of plastic.

AI as the Solution

Genpact is prioritising AI and positioning itself as an AI-first company. This means that whenever a company approaches them with a problem, they first ask their team to consider how AI can be applied to solve the problem.

Interestingly, Genpact’s AI-focused approach is paying off. In its Q2 2024 earnings, the company posted promising numbers with data-tech-AI contributing $546 million, or 46%, to the quarter’s total revenue.

However, DeLussey warned against a one-size-fits-all approach to AI. He noted that while some companies are leading with AI, others need to adopt it gradually. The key is to understand how AI can fundamentally transform work and then strategically implement it where it can deliver lasting value.

Watch the full keynote here.

Genpact, in collaboration with HFS Research, recently released a report called The GenAI Countdown. The report highlights a notable concern: Many businesses are narrowly focusing on productivity, potentially negatively impacting employee experiences and stifling broader innovation.

The report stated that 52% of respondents expressed concerns that an overemphasis on productivity could lead to a negative impact on employee experiences​​.

Genpact’s global head of AI/ML practice, Sreekanth Menon, said that companies should not pursue productivity just as an end goal but as a critical step in a broader, more strategic GenAI journey. 

“We’re initially focused on leveraging GenAI for internal improvements and productivity because this will give us the confidence to expose it to our customers, knowing our internal experts have thoroughly tested it,” said Menon, saying that this initial focus on productivity builds trust and internally verifies the technology’s reliability before implementing it in broader, more impactful ways. 

In a bid to gain deeper insights into GenAI’s long-term value and the risks of overemphasising immediate outcomes such as productivity improvements, HFS Research, in partnership with Genpact, a global professional services firm, surveyed 550 senior executives worldwide. 

These respondents represent organisations with revenue exceeding $1 billion across 12 countries and eight industries. For further insights, they conducted in-depth interviews with ten enterprise leaders at the forefront of GenAI adoption and innovation.

Click here to check out the interactive dashboard. 

Here are some key highlights and takeaways from the report: 

• Most companies are early in their GenAI journey but are making significant investments, with 61% of executives allocating up to 10% of their tech budgets to GenAI, alongside a 30% increase in generative AI funding over the next year. 
• There is a significant shift toward partnerships for building GenAI capabilities, with 45% investing in technology providers specialising in GenAI solutions​​.
• Top challenges include data quality or strategy (42% for IT leaders) and a lack of a structured GenAI plan (46% for business leaders)​​.
• 36% of executives reported a shortage of skilled professionals. 
• Organisations are a bit hesitant about data sharing, with only 16% of enterprises using their proprietary data. 
• 80% of executives recognised the need to transition to performance- and purpose-driven commercial models, moving away from traditional time-and-material models​​ with partners to fully capitalise on GenAI’s potential. 
• 74% of executives believe that GenAI will inspire new and disruptive ways of value creation within their organisations​​.

HFS Research CEO and chief analyst Phil Fersht described GenAI as “the first real innovation to disrupt industry since the advent of the internet,” suggesting that it’s transforming business interactions and operational models.

Overall, these insights reflect GenAI’s growing importance in reshaping business strategies and the imperative to adopt a balanced approach that integrates technology with human-centric frameworks.

MathCo announced the appointment of NV Tyagarajan, aka Tiger Tyagarajan, as a board member, effective April 2024.

Tyagarajan brings a wealth of invaluable experience and visionary leadership to MathCo. Renowned as an industry luminary, Tiger has a distinguished track record of steering companies toward success through future-proof business strategies, promising to enhance its client offerings significantly.

His appointment as a board member signifies a pivotal moment in MathCo’s journey, as the company looks forward to leveraging Tiger’s profound insights and industry acumen to propel its growth trajectory.

“Having studied MathCo’s journey since its inception, I have been thoroughly impressed by its evolution into a mature and resilient organisation, delivering impactful solutions to leading global enterprises.

“Their strategy of building and deploying a proprietary platform, NucliOS, with pre-built workflows and reusable plug-and-play modules that empower clients to achieve the vision of connected data-driven intelligence, is truly impressive. I am delighted to join MathCo’s board and eager to collaborate with Sayandeb, Aditya, Anuj, and the passionate MathCo team,” Tyagarajan said.

Tiger is best known for his pivotal role in transforming a division of General Electric (GE Capital International Services) into Genpact and his thirteen-year tenure as CEO of the company.

His influence extends across leading consulting, AI, and technology firms, where he serves as an advisor, contributing to shaping organisational futures, fostering sustainable growth, and championing transformative initiatives.

Genpact has announced a collaboration with Microsoft aimed at driving modern finance transformation across enterprises. The collaboration focuses on leveraging data, technology, and AI to fuel innovation for finance organisations globally.

The collaboration aims to harness the power of Microsoft Azure OpenAI Service coupled with Genpact’s deep domain expertise, data capabilities, technology, and AI proficiency to transform finance organisations into future-ready entities. This initiative is geared towards enabling quicker decision-making supported by a solid foundation of data and AI.

Balkrishan “BK” Kalra, President and CEO of Genpact, stated, “Genpact has decades-long expertise and leadership in finance and accounting services. Our strategic collaboration with Microsoft will drive the next wave of finance transformation using AI to turn finance functions into strategic, data-driven operations that support growth and competitiveness.”

Genpact’s responsible use of Azure OpenAI Service is already showing promising results in modernising finance functions globally, providing businesses with faster access to insights and helping create a modern, actionable finance data and analytics strategy.

Nicole Dezen, Chief Partner Officer at Microsoft, commented, “AI is revolutionising the finance industry by enabling unprecedented levels of efficiency, accuracy, and innovation. We are thrilled to partner with Genpact to combine their domain expertise with Microsoft Azure OpenAI Service to empower finance organisations to harness the power of data to drive business transformation.”

Genpact is not only driving transformation in finance organisations but is also modernising its own finance function through extensive use of Microsoft’s AI tools. By harnessing the power of data, technology, and AI, Genpact has achieved significant results across multiple areas of finance:

• Enhanced vendor management automation with advanced AI algorithms has led to a 85% accuracy in response and doubled supplier satisfaction. Real-time communication, coupled with this data-driven approach, is driving favourable deal negotiations and reduced disputes.
• The customer collections process has been transformed with AI-powered analytics and automation, along with streamlining of invoice and payment tracking.
• Implementation of a large language model-based digital assistant, utilising advanced natural language processing (NLP) and machine learning (ML), has streamlined tax document submissions, resulting in a 53% reduction in support tickets and significantly improving employee experience.

In September last year, Genpact collaborated with AWS aimed at revolutionising financial crime risk operations through the integration of generative AI and LLMs. The partnership entails the integration of Genpact’s cloud-based financial crime suite, riskCanvas, with Amazon Bedrock, yielding significant efficiencies and benefits for clients, including Apex Fintech Solutions.

Genpact has announced the opening of its AI Innovation Center in Gurugram, India, in collaboration with NASSCOM.

The centre aims to democratise AI, fostering world-class AI talent to support India’s ambitions in the field and apply AI solutions at scale for clients globally.

As part of Genpact’s AI-first approach, the centre will serve as a hub for innovation, enabling talent to learn, experiment, and develop comprehensive, AI-focused solutions to drive growth for Genpact’s global clients.

The AI Innovation Center provides Genpact experts and clients with a dedicated space to explore new ideas, capabilities, and solutions. Clients will have increased access to Genpact’s deep business knowledge, combined with the data, technology, and AI expertise of its personnel, as well as industry partnerships.

Piyush Mehta, CHRO, and Country Manager, India, Genpact, emphasised the importance of fostering a culture of learning and experimentation. He stated, “By fostering a culture of learning, experimentation, and using the best of our partner ecosystem, we’re empowering our employees to become co-creators alongside AI. We believe data, technology, and AI, as well as our talent, are key to driving unparalleled outcomes for our clients, and with this AI Innovation Centre, we’re not just embracing the future, we’re shaping it together.”

India has been accelerating its AI innovation journey, with the government launching a $1.2 billion IndiaAI mission to promote capacity building, AI literacy, establish research centres, and create legal frameworks for the responsible use of AI.

Genpact’s AI Innovation Center will democratise access to AI and cultivate world-class AI talent in India. With over 125,000 employees, Genpact aims to empower its workforce to leverage advanced technologies and drive lasting value for clients.

Debjani Ghosh, President, NASSCOM, highlighted the significance of this initiative, stating, “This initiative not only showcases the technology industry in India’s commitment to becoming a global leader in AI but also demonstrates its potential to innovate and contribute to the global AI ecosystem.”

Genpact launched its inaugural AI Innovation Center in London last year, with several more centres planned across the world in the coming months.

Genpact has announced a significant expansion in the role of its Chief Human Resources Officer (CHRO), Piyush Mehta. Effective immediately, Mehta will also assume the responsibilities of Country Manager for India, signalling the company’s deepening commitment to innovation, growth, and talent development in the region.

The decision reflects Genpact’s steadfast dedication to India and its strategic shift towards becoming an AI-first organisation. In the previous year, Genpact established and expanded three new operational centres in Tier 3 cities across India, such as Madurai, Jodhpur, and Warangal. 

This expansion not only broadened the company’s talent pool and geographic footprint but also contributed significantly to the local economic landscape.

BK Kalra, President, and CEO of Genpact emphasised the importance of India as a critical talent market, stating, “India remains a strategic talent market for Genpact, and we believe people are the greatest assets for us and our clients.” He praised Mehta’s extensive experience in nurturing talent ecosystems over the past 25 years and expressed confidence in his ability to bolster Genpact’s presence in India.

In his former role as CHRO, Mehta played a pivotal role in shaping Genpact’s human resources strategy. Now, with his expanded responsibilities, he aims to leverage his expertise to further drive the company’s AI-first approach in India, delivering value to key stakeholders while continuing to oversee the global HR function.

Expressing enthusiasm for his new role, Mehta affirmed, “India’s talent has always been a prime differentiator for economic growth in the country. I am excited to take on this expanded role as we continue to grow our business, empower India’s talented workforce, and contribute to the country’s economic landscape.”

In a move signalling its commitment to digital transformation, Genpact announced today the appointment of two new executives to its leadership team. 

Vipin Gairola has been named Global Operating Officer, while Vidya Rao assumes the role of Chief Technology and Transformation Officer. These appointments underscore Genpact’s dedication to leveraging data, technology, and AI-first principles to drive growth.

As the newly appointed Global Operating Officer, Vipin Gairola will spearhead the transformation of service delivery for Genpact’s clients through AI-led solutions. With extensive experience garnered from senior leadership roles at Accenture over the past two decades, including his recent tenure as Chief Strategy Officer for Accenture Operations, Gairola brings a wealth of expertise to Genpact. 

In his new capacity, he will oversee the company’s global client operations, analytics, data, and technology initiatives, solidifying his position as a key figure within Genpact’s Leadership Council.

Meanwhile, Vidya Rao, formerly Genpact’s Chief Information Officer, assumes an expanded role as Chief Technology and Transformation Officer. In this capacity, Rao will lead the charge in reimagining Genpact’s internal processes, tools, and infrastructure with an AI-first approach. 

Additionally, she will be instrumental in establishing a robust data office to enhance Genpact’s data capabilities, enabling the company to derive actionable insights to drive its AI and Automation initiatives forward.

Commenting on the appointments, BK Kalra, President and CEO of Genpact, expressed enthusiasm for the new additions to the leadership team. “We are excited to have highly talented and transformative individuals in key leadership roles at Genpact,” said Kalra. “Vidya and Vipin’s appointments emphasise our ongoing strategy to re-energize our leadership team to drive us into our next chapter of growth.”

The appointments of Gairola and Rao underscore Genpact’s strategic focus on harnessing the power of data, analytics, operations, and AI to drive innovation and steer both the company and its clients towards success in an AI-driven world.

Genpact has announced its collaboration with Amazon Web Services (AWS) and Amazon Business to redefine the property loss replacement and claims management approach. 

Leveraging its extensive claims management expertise, Genpact is integrating Amazon Bedrock‘s generative AI capabilities and Amazon Business procurement API integrations to streamline the claims submission process. 

Check out more details here.

This advanced pricing automation workflow aims to reduce the submission timeline from weeks to days, focusing on efficient replacement item identification and timely delivery of policyholder estimates.

Sameer Dewan, global operating officer at Genpact, emphasised the transformative impact of AI on the insurance industry, stating, “AI is fundamentally reshaping the landscape of the insurance industry. Our Genpact AI-driven automated pricing workflow, powered by AWS, is transforming the research, significantly reducing the time adjusters spend investigating by as much as 75 percent. By automating routine tasks and enhancing decision making, our AI solution is empowering smarter pricing decisions, expediting claims settlements, and bringing about a profound transformation in the customer experience.”

Genpact aims to deliver measurable value to its clients through ongoing innovation. Future plans involve the integration of additional AI services into the automated workflow, including real-time summaries of market values for claimed contents and optimal action recommendations for further processing.

Recently, Genpact also announced an expanded collaboration with AWS aimed at revolutionising financial crime risk operations through the integration of generative AI and LLMs. The partnership entails the integration of Genpact’s cloud-based financial crime suite, riskCanvas, with Amazon Bedrock, yielding significant efficiencies and benefits for clients, including Apex Fintech Solutions.

Read: Bedrock is All About Choices

Genpact has unveiled its leadership succession plan. Tiger Tyagarajan, who currently serves as the President and CEO, has informed the company’s Board of Directors of his retirement intentions, which will take effect on February 9, 2024. In response to Tyagarajan’s retirement, the Board has appointed Balkrishan “BK” Kalra, Genpact’s Global Business Leader for Financial Services and Consumer & Healthcare, as the next CEO. 

Kalra is set to join the Board on the same date, while Tyagarajan will continue as a member of the Board of Directors. BK Kalra is a seasoned business leader with over three decades of experience in aiding companies’ growth, from their early stages to becoming global competitive enterprises. 

Having joined Genpact in 1999, he has held various leadership roles within the organisation. Kalra is responsible for overseeing Genpact’s global transformation efforts in industries such as banking, capital markets, consumer goods, retail, life sciences, and healthcare, facilitating companies in effectively harnessing technology and AI-enabled solutions.

James Madden, Chairman of Genpact’s Board of Directors, expressed his satisfaction with the leadership change, stating, “We are delighted to announce BK as Genpact’s next CEO, a leader with a proven track record of delivering business results and fostering deep client relationships. In planning for Tiger’s retirement, the Board undertook a robust process, assessing a number of internal and external candidates. In the end, BK stood out as the natural successor. 

Madden highlighted that Kalra understands the importance of investing in emerging trends and technologies with a particular focus on Genpact’s efforts around advanced analytics and AI-enabled solutions. “BK’s strategic vision and deep understanding of our clients and business is exactly what Genpact needs as we enter this new chapter.”

Expressing his enthusiasm, Kalra said, “I am honoured to assume the CEO role and appreciate the confidence and trust that Tiger and the Board have placed in me. With an immensely talented workforce and a deep history of developing innovative solutions for our clients, Genpact has a unique opportunity to lead our industry. I look forward to working closely with the Board and our leadership team to accelerate a new chapter of growth for Genpact, one with technology at the forefront of everything we do to unlock tremendous potential for our clients, employees, and shareholders alike.”

Tiger Tyagarajan, who took on the CEO role in 2011, has played a pivotal role in leading Genpact through a period of remarkable growth. Under his leadership, the company transformed into an industry leader with annual revenue exceeding $4.3 billion in 2022, primarily by leveraging data and technology to enhance client services.

James Madden acknowledged Tyagarajan’s contributions, stating, “On behalf of the Board and the entire organisation, I would like to express our sincere appreciation for Tiger’s leadership of Genpact over the last 12 years. Tiger has built a strong, diverse, and global team, focused on a clear set of prioritised verticals, geographic markets, and services. We look forward to his continued contributions on the Board.”

Tyagarajan expressed his gratitude, saying, “Leading Genpact has been the highlight of my career, and I would like to thank the entire team for their support. The world is rapidly changing around us, and I am incredibly proud of what we have achieved, staying ahead of the curve as a true partner to our clients around the world, empowering our employees, and transforming the communities in which we live and operate. BK has been an integral part of Genpact’s success, and I am confident that, under his leadership, we are well positioned for the next phase of our journey and future growth.”

Also read: Genpact, NASSCOM Partner to Bring Generative AI Playbook

Generative AI is rapidly becoming a transformative force in various industries. That is why Genpact, in collaboration with NASSCOM, has unveiled an essential playbook designed to demystify and harness the power of this technology. 

Click here to check out the playbook: FMOps.

Genpact and NASSCOM have recognised the challenge that enterprise leaders go through for grappling and adoption of generative AI. Thus, both have joined forces to provide a comprehensive guide, equipping organizations with the knowledge they need to develop effective generative AI solutions.

The topics included in this playbook highlight the importance of generative AI, how to adopt it, and how to make a winning generative AI solution.

This collaborative effort brings together insights from experts across various industries, presenting a detailed compendium that not only illuminates best practices but also highlights the critical aspects of managing and mitigating the risks and challenges associated with artificial intelligence as businesses scale their operations.

The playbook provides industry insights on building successful generative AI solutions, offering best practices for setting up, managing, and scaling generative AI operations. It aims to help stakeholders understand foundational model operations, anticipate and address associated challenges, and streamline the development and deployment of language model applications through LLMOps, making generative AI adoption more accessible.

Sreekanth Menon, Global AI/ML at Genpact, encapsulates the essence of this invaluable resource, stating, “This study serves as a companion guide to building ethical and feasible generative solutions at scale. It offers a blueprint for building tool stacks, frameworks, and governance mechanisms that will bring the enterprise-grade pilot projects to production.”

In an age where the power of Generative AI is undeniable, the Genpact and NASSCOM partnership aims to be the guiding light for businesses seeking to harness this transformative technology, ensuring they do so responsibly and effectively. This playbook offers a comprehensive resource that unlocks the full potential of generative AI, turning it into a winning solution for enterprises worldwide.

Read: Genpact Embraces AI Guru for its Employees

In a world where organisations are looking at short term goals when adapting or implementing generative AI solutions, Genpact believes that it’s time they started focusing on long term returns. Katie Stein, the chief strategy officer at Genpact said that organisations are getting on the edge in implementing these solutions. 

She also shared Genpact’s generative AI strategy on how they are scaling and deploying them responsibly. “I would argue that generative AI is our moment of fire, our moment to change and transform how businesses run and to change society.” she said. 

Drawing a comparison of how society changed with how humankind evolved after the discovery of fire she explained, “Something fundamental changed with the introduction of ChatGPT. It truly democratised and consumerised AI. It changed how the average person thinks about AI and engages with it.”

She acknowledged that this is just the beginning, and also the hard phase of the development of AI, but all of this would eventually determine how we progress with AI.

On the contrary to the popular obsession with productivity and AI, Stein warned about the dangers of hyperfocus on just AI productivity, and immediate result. “I hear a lot about productivity. And I will say the hyper focus on productivity is dangerous, limiting and will leave AI in the same station,” she added.  

She reasons that so much digital transformation should be thought of as end-to-end solutions and not just immediate outcomes. And as a result, companies are rushing to optimise and put in point solutions. 

She also said that the companies need to step back and reimagine the kinds of outcomes, the economic values that AI can create for them and maybe even completely change the way they collaborate or work with different models – “not just for the immediate future but in the long run.”

Towards Inclusive and Responsible Generative AI 

As the fear continues to grow around AI replacing people, Stein touched upon certain points during her talk suggesting an inclusive way for corporations to move towards AI advancements. 

She urged for organisation, whether it’s through external parties, or through in-house platforms to think about how they decide to skilling at scale for the emerging roles. 

“So when I think about the skills that are going to go into this next phase, it’s a new set of skills, you have prompt engineers. But we also need more experienced designers to make better user interfaces and extend experience. We need architects, we need strategists. There’s many roles we need to train and create” she advised. 

Stein who has been with Genpact for almost a decade now, further shed light upon ways organisations should pick AI models as per their need instead of jumping on the bandwagon as others.

“Many organisations haven’t yet understood how fundamental this change is for them,” she said. “At Genpact we’re working with our responsibility AI framework, which has the foundational elements around security and privacy,” Stein added. 

She raised several significant questions — how do we make sure there isn’t bias in models as we train them? How do we make sure that bias does not creep in as we use AI for HR or recruiting? How do we monitor that going on? 

Further, she suggests for organisations to build responsible AI they need to put in place terms, strategies, metrics and guardrails that can be used for the base. 

Lastly, she spoke about the role of globalisation in the regulatory framework. In the last one year government bodies around the world have begun the dialogues to come up with regulations for AI. “It is very unsure at this stage, and will continue to evolve and fit,” Stein concluded. 

Genpact has announced an expanded collaboration with Amazon Web Services (AWS) aimed at revolutionising financial crime risk operations through the integration of generative AI and LLMs. The partnership entails the integration of Genpact’s cloud-based financial crime suite, riskCanvas, with Amazon Bedrock, yielding significant efficiencies and benefits for clients, including Apex Fintech Solutions.

Leveraging its existing relationship with AWS, Genpact is merging its intellectual assets and industry expertise with AWS’s generative AI capabilities. The seamless integration of Amazon Bedrock FMs into Genpact’s riskCanvas financial crimes software suite aims to unlock substantial value, enhance speed, and improve accuracy in detecting, investigating, and preventing financial crime threats for businesses.

This integration enables experts to review outputs and adopt a guided decision-making process, offering comprehensive summaries and analyses of potential financial crime activities. This results in improved efficiency and precision.

Genpact has actively engaged with numerous riskCanvas clients to enhance the detection, investigation, and prevention of various financial crime threats. As a result, Genpact is delivering accelerated efficiencies and significant impact to clients in the finance and capital markets sectors, with a notable example being their collaboration with Apex Fintech Solutions.

Justin Morgan, Head of Financial Crimes Compliance at Apex Fintech Solutions, emphasised the importance of staying ahead of financial criminals: “With the addition of generative AI features to Genpact’s riskCanvas, our analysts will be able to produce Suspicious Activity Report (SAR) narratives and case summaries at the click of a button using inputs from millions of data points. We expect this will reduce time spent on case summarizations by 60%, allowing our analysts to spend more time identifying truly suspicious financial activity.”

By utilising approved client data from the secure riskCanvas ecosystem and Amazon Bedrock’s secure data handling capabilities, highly accurate outcomes are generated while maintaining robust data protection standards.

Atul Deo, General Manager, Amazon Bedrock at AWS, emphasised the importance of responsible AI implementation: “Amazon Bedrock is rooted in secure data handling, encrypting all data and allowing users to customise models privately. Integrated with Genpact’s riskCanvas, this powerful combination enables our mutual customers to enhance productivity in investigating, detecting, and preventing financial crime threats.”

BK Kalra, Global Business Leader, Financial Services, Consumer and Healthcare at Genpact, highlighted the growing need for generative AI in financial crime operations: “Genpact’s expanded relationship with AWS represents a pivotal step in redefining the operations landscape for enterprises. Together we can unlock untapped value, and fuel significant growth opportunities for our clients, solidifying our commitment to delivering valuable business impact.”

Genpact announced that it has incorporated generative AI capabilities into its proprietary Enterprise360 intelligence platform leveraged by clients worldwide.

Enterprise360 is Genpact’s cutting-edge platform for managing and transforming client operations. The platform brings together digital tools, standardised processes, and now the power of generative AI to help businesses identify and address operational issues and optimise performance. 

With access to replicable solutions and a wealth of data-driven insights, teams can expedite value delivery and drive transformative change, while leveraging actionable feedback and fostering a culture of continuous improvement.

Enterprise360 is used across Genpact’s global talent serving over 800 clients globally. Enterprise360 helps businesses digitise critical operating rituals and provides visibility into almost 500 metrics and more than 250 benchmarks.

“The integration of generative AI into Enterprise360 is a significant milestone for Genpact. This new capability will help our clients drive even greater performance and transformation, and we are excited to see the impact it will have on their businesses.

“From design to operations, transformation to renewals, Genpact’s Enterprise360 offers comprehensive solutions that address the complete lifecycle of client requirements,” Vidya Rao, Chief Information Officer, Genpact, said.

Analytics India Magazine’s much-lauded women-in-tech conference saw participation from over 500 attendees, 50 speakers and 200 firms. The 5th edition of ‘The Rising 2023’ featured inspiring stories of women from different backgrounds over two days. 

The power-packed event concluded with the ‘Best Firms for Women in Tech Awards’ that recognises companies that have implemented successful programs to promote diversity, provide equitable opportunities for career growth, offer coaching and mentorship to women, and help close the gender pay gap. Sagarika Ghose, the renowned award-winning journalist and author, handed over the awards on behalf of AIM.

Let’s take a look at the winners.  

Genpact

Genpact fosters an inclusive culture by offering paid leave and supportive resources for working parents. It actively pursues diverse talent through campus recruitment and partnerships with minority organisations. The company also sensitises its hiring teams through unconscious bias training and inclusive language practices.

Lowe’s 

Like Genpact, Lowe’s prioritises an inclusive workplace for women associates, offering equal opportunities for career growth and implementing programs to address the barriers before and after joining the workforce. They prioritise equity over equality to ensure all associates have the resources they need to succeed.

Verizon Data Services India Pvt Ltd (Verizon India)

An early adopter of the Maternity Benefit Act, 1961, Verizon Data Services leads in diversity and inclusion and adapts to changes in maternity benefits. It launched the ‘WINGS’ program in 2016, supporting women returning to work after a career break and addressing hiring biases.

Futurense Technologies

Futurense values and supports its female employees throughout their lives, and this includes even those on a career break. They prioritise potential over current capabilities in hiring and have achieved gender equality in their leadership team. The company values diversity and has initiatives to support women from Tier 2 and Tier 3 cities, offering free accommodation and mentorship to those relocating for work.

TheMathCompany Inc

Joining the winners is TheMathCompany, which offers inclusive parental leave, and period leave and is committed to diversity, equity, and inclusion. Its DE&I team conducts research, advocacy, and training on leadership awareness and unconscious bias programmes. The company supports employee resource groups and offers annual medical check-ups, with a special package for women.

Wipro

Wipro has a policy for holidays, time off, and parental and adoption leaves. They also have a program called ‘Begin Again’ for women returning to work. Wipro ensures equal employment opportunities for all and supports gender equality and women’s empowerment through the ‘UN Women Empowerment Principles’.

Continental Automotive Components – Technical Center (India)

Continental Automotive Components is dedicated to gender diversity and inclusion, with successful strategies to promote women in tech. They started Launch-Pad, a six-to-nine month program under which they hired 16 women on career breaks up to five years, providing on-the-job training, technology learning, and mentoring.

Fractal Analytics

Fractal prioritises diversity, equity, and inclusion in the workplace. They offer unlimited leaves and a gender-neutral program, ‘ReBoot’, for those transitioning back to work. Additionally, an AI chatbot supports employee well-being and active listening.

ABInBev 

ABInBev is our next winner for promoting diversity, equitable career growth, closing the gender pay gap, and offering various leave options for primary caregivers. They also have a ‘Ramp On’ program for returning mothers and several benefits, including enhanced maternity coverage and support for childcare and elderly care.

DBS Technology Services 

DBS is committed to supporting women. Their key initiatives include a grievance redressal policy, women’s security sessions, an emergency safety service app, and the ASCEND program offering coaching and mentorship. They also run the MyPersona women leadership development program, graduating 11 women in 6 years.

Tata AIA Life Insurance

Tata AIA Life Insurance promotes diversity and inclusion in the workplace through programs that support career growth, coaching and mentorship, and work on closing the gender pay gap. They provide extensive support to employees, including maternity leave, medical aid, emergency funds, and flexible work hours. Women employees also have access to specific programs and leave options. 

LTIMindtree

The next winner, LTIMindtree values and supports their female employees through extensive leave policies, prevention of sexual harassment training, gender pay parity, and work-from-home flexibility. They also have a women-specific community for support and engagement in career development and well-being.

Sify

Sify prioritises diversity, equity, and inclusion in their workplace by empowering and uplifting women. They’ve taken various actions to provide equal opportunities, such as reviewing budgets to prioritise hiring women, creating referral programs, and participating in hiring events for women.

The Machine Learning Developer Summit 2023 has come to a close, with some of the industry’s leading AI and ML practitioners from companies like Google, Intuit, Optum, Genpact, and more coming together to offer valuable insights on the state of the industry today. 

MLDS 2023 was a developer’s paradise. From tech talks on state-of-the-art techniques used by tech giants, to workshops that build practical knowledge of industry-leading tech, to paper presentations that offer a look into the cutting-edge of ML research in India, the conference offered something for every developer and data scientist.

Rajeev Balakrishnan, a developer attending the summit, had this to say about his experience.

“As a developer, I feel like I am in my element. I’m very comfortable in the environment that MLDS creates for developers, and I feel like I am in my community and feel the need to upskill and catch up with the rest. MLDS allows developers like me to get valuable insights from some of the most well-known industry leaders.”

The conference featured a multitude of talks over the course of two days. From describing an approach on how to integrate ML into everyday workflows, to a session on solving for a information-centric approach on AI, to a talk on topic modelling functionality using generative AI, speakers brought a lot of insights to the table about the growth of the AI and ML industry. 

Some developer favourites included Parikshit Nag’s talk on the art of personalisation which showed ML engineers how to deploy a recommendation engine for product design, and Soumen Ray’s talk on AGI and humans’ evolution in the next decade, which explored the concept of a general intelligence and the impact it can have on humanity.  Other notable talks include Amit Kumar’s session on how developers can use NVIDIA’s solutions to build and deploy accelerated data science solutions, and Rohit Shetty’s talk on using low-code tools to upskill citizen data scientists to keep them updated with latest industry trends. 

We also had a handful of workshops during the event that allowed developers to get hands-on with new technologies in computer vision and methods to train new algorithms. They also learned about using transformer models for computer vision, automating analytics for a better data pipeline, and how to use cloud services to scale MLOps.

MLDS also provided a platform for AI and ML researchers to present their research papers. Industry leaders from the research wings of companies like Elsevier, TATA Elxsi, Siemens, Bio, Intel, Uber, and more came to present their papers to the ML community. These sessions were very lively and involved a lot of questions from inquisitive developers in the audience. 

Some fan favourite papers included an approach beyond traditional vibration classification, clinical relation prediction using a graph-based model, a new clustering technique for faster processing of large unstructured data, and a new way of building a real-time ML inference platform for AIOps. 

One of the biggest crowd-pullers for the conference was the talk by Sudalai Rajkumar, a data science superstar and 4x Kaggle Grandmaster. He spoke about AI in Web3 and its applications. Alongside this talk, the team behind MachineHack featuring Abhijeet Katte and Krishna Rastogi spoke about how to build your own brand as a data scientist.

To cap off the eventful conference, MLDS hosted Abhinav Bindra, the Golden Boy of Indian shooting and tech entrepreneurship, for a fireside chat on his journey as an Olympic gold medallist. The former world champion spoke about his journey to becoming one of the world’s best shooters, and the interesting intersections between tech entrepreneurship and training for an Olympic sport as precise as shooting. To acknowledge the up-and-coming stars of the Indian data scientist community, MLDS honoured 40 of the country’s top data scientists with the 40 Under 40 Data Scientists awards distributed by Mr. Bindra.

Abhijeet Katte, Chief Growth Officer at MachineHack, expressed his feelings about the conference, stating, 

“MLDS is all about the technical side of the machine learning community, and it’s a great place to interact with the developers of the industry. The talks are also enriching and can give ML practitioners the competitive edge they need to make their next big project.”

If you didn’t have a chance to attend this premier conference for developers, don’t worry! We have more exciting events coming up, with the next one being The Rising 2023, which aims to shine a spotlight on women in tech. Our flagship conference, Cypher, will be announced later this year, so stay tuned to AIM to know more. 

At present, the world is transitioning in three significant ways—for geopolitical and socio-economic world order; the shift towards a low carbon economy; and the scalable deployment of AI. Sanjay Srivastava, chief digital officer of Genpact, interacted with Analytics India Magazine and shared how their firm is enabling Fortune 500 companies across the globe with data analytics and AI in these three dimensions.

In December, Bloomberg reported that all the packaging and waste material from Amazon ends up getting burnt in India. This highlights the broken recycling system and how companies outsource their emissions to another country, ultimately making their emission untrackable and shine without flaws.

Srivastava gives an example of a company that spent approximately 24 months to shift their computer to the cloud, with the key objective of reducing their carbon footprint. The company did intricate calculations to measure the exact reduction they would achieve with this and were finally able to achieve that and publish the numbers. “The company missed out on a major factor, the disposition of the existing computers and systems has a carbon impact as well, which needs to be added back,” explained Srivastava. 

But this is not because the company planned to miss it, it is because they did not know that it is a question that they have to ask. This is where AI and ML tools come into the picture. “These technologies help us bring out the questions that we did not know we have to ask and are proving to be very important now”, said Srivastava.

“Think about carbon footprint comprehensively, and not conveniently”

“Climate is at the top of our client’s agenda list,” said Srivastava. He said that Genpact is in front of three services—data extraction, analytics, and change management. 

First order of execution is extracting data from the locked up places like unstructured documents and classifying them for use and harmonising it. “Every company has tons of data, but the problem is that it is very messy, and most unavailable and locked up,” explained Srivastava. To this end, the firm leverages natural language processing models to extract information.

The second step—analytics—is what Srivastava calls the ‘shipping lane’. Now that the data is structured and managed, predicting and recommending information from the data to the companies allows them to ultimately reduce carbon footprint. Thinking of it like the journey or supply chain of a consumer product from one country to another. Genpact enables the company to analyse the emissions at each step of the chain and, thus, contributes to reducing the components that maximise the emissions.

Change management is the step where AI/ML plays the biggest role. “We can track the journey of a product to your footsteps and give you insights to choose options that enable you to offset your carbon footprint,” said Srivastava. 

Moving Beyond Budget

What ends up occurring is that a lot of companies get these analytics and prediction engines but they don’t do it as it is not something that can be done from a top-down approach—it has to be done individually. Srivastava gives another example of how companies keep replenishing products every year without asking the employees. “We have to ensure that we are not forcibly replenishing everyone’s phones, for example, because of some annual contract”.

According to Srivastava, this is an important discussion and has been increasing in the past 5–10 years. “It’s not happening because of the budget. It’s happening because of the carbon footprint, it’s happening because it makes an impact.”

Since Genpact is a professional services firm that does not undertake manufacturing and holds warehouses, Srivastava believes that they are in a better position in terms of carbon baseline. “We are not clean, but we are better off because we do not have a manufacturing footprint.”

Genpact believes that the societal and governance aspect 0f ESGs is as important as the environment. The company has trained around 50,000 people by providing them domain knowledge along with offering courses. “Governance is night and day,” said Srivastava. “We deal with Fortune 500 companies and any mistake can bring the company to a halt. So, governance is as important as anything else for us.”

Partnership with Climate Vault

Genpact’s partnership with Climate Vault takes the approach even further and pushes towards a very important objective. “There has been a lot of greenwashing in the market,” said Srivastava. It is not clear if the numbers put forward by the companies are accurate. These numbers can be exaggerated and oftentimes are just for marketing the goodness.

What climate vault does is, instead of going to the voluntary market of carbon credits, it goes into the regulatory market. For instance, if a company has to build a power plant, they would have to buy credits from the government before they can actually start the process. Climate Vault buys 100 of these credits from the climate market so that other companies cannot buy it. This results in reduction in the carbon emissions from the market as a whole.

Climate Vault has another initiative for offsetting carbon dioxide. Their unique approach is trapping carbon dioxide from the atmosphere, encapsulating it, and burying it into the ground for 150 years. This is because they believe that stopping carbon emissions is not enough, as we have damaged the environment enough. Being carbon negative is the next step but also that this process is very expensive.

Genpact powers up Climate Vault by integrating them onto their platform and into different engines, along with bringing their clients into the ecosystem. The partners are also building an API to enable companies to measure the carbon offset of the product they are selling. Thus, making Climate Vault scalable.

The rising demand for skilled workforce across sectors has made it increasingly challenging to hire and retain top talent and, more so, from the top campuses. To address the ongoing ‘talent war’ and attract & upskill campus recruits at speed and scale, in 2022, Genpact launched SkyDive – Global Campus Academy, a 3-month long persona-driven experiential program offering immersive learning at the intersection of the domain, data analytics and professional skills. 

What Makes SkyDive a Distinct Campus-to-Corporate Program?

SkyDive offers a unified platform for our campus recruits to immerse themselves in a culture where great minds, next-gen technology, and astute business acumen intersect to accelerate the Data-Tech-AI-led growth at Genpact.

The program has been designed on a key principle of building hyper-specialized and persona-based talent. It enables the development of critical digital and cognitive capabilities, social and emotional skills, and, most importantly, adaptability and resilience.

The three skill-based Analytics personas include:

1. Data Engineering 
2. BI, Reporting and Data Visualization
3. Advanced Analytics (AI/ML, Stat Modeling)

The Key building blocks of SkyDive are:

1. Back to Basics: Micro-learning nuggets to build foundational skills (starting from MS Excel, SQL, and Statistics) and form a baseline for the topics to be covered during the program. 
2. Expert Masterclasses: In-depth, hands-on persona-driven instructor-led workshops to reinforce the concepts learned during self-learning and an opportunity to get technical queries addressed.
3. Industry Colloquium: A unique opportunity to learn about the latest industry trends from experts within and outside the firm
4. Hands-on integrated labs: Focused time to practice tools and platforms crucial for the business.
5. Ignite-Innovate-Invent: To incubate an entrepreneurial mindset and ability to face the clients confidently, the participants are given a real-life business problem to craft a solution, keeping in mind key parameters like commercial viability, business value, ease of conducting business and more. Towards the end of the program, each cohort (of 5) presents their solution to a panel of SMEs who critique and discuss opportunities to improvise the outcome in a typical shark tank format.     
6. Gravitas: For overall holistic development, the participants undergo intensive personality development to learn how to communicate with confidence, influence, and authority.
7. Campus to Careers: An informal platform to interact with the previous campus hires to get a sneak peek into life at Genpact, career trajectories, and challenges faced. These 30 minutes open forums were eye-opening and inspiring at the same time and invited maximum participation.
8. MentorMe: A 6-month long mentoring & buddy program to help through the onboarding journey and facilitate a smooth transition into the corporate world
9. Joy@Work: To keep the fun element alive, the campus hires conducted innovative and fun activities, including birthday celebrations, dumb charades, quizzes, contests, Friday Fun and more throughout the program.

The SkyDive Class of 2022 comprised 500+ fresh minds from renowned colleges in India and the US, ranging from NIT, BIT, VIT, Indiana University, and Boston University. 

Six batches were held from June to October 2022, comprising campus hires holding B.Tech., MBA degrees and Science, Stats, and Economics graduates.

To learn more about career opportunities at Genpact, click here.

In association with Analytics India Magazine, Genpact, a global professional services firm delivering digital transformation, will take you inside the world of data, analytics, and AI at its virtual career fair on Saturday, September 03, 2022. 

Designed as a networking opportunity, this event will bring together business leaders and other analytics experts to share their experience working in the field. Plus, you’ll learn about Genpact’s latest analytics initiatives, including DataBridge, a program designed to upskill and train 100,000+ employees in data science techniques. 

So, if you’re looking to start a career in analytics, or are merely curious about the industry, join us for this exciting event. Attendants will participate in workshops, hackathons, and coding challenges while exploring various data analytics career paths. Most importantly, this is your chance to showcase your skills and talent to Genpact’s hiring managers. 

Genpact Analytics Career Day: https://genpactcareerday.com/

With more than 40 data experts across industries attending, these immersive sessions will show you how advanced analytics transform enterprises’ operations today and into the future. 

To register for this unique opportunity, click here. 

• Discover why Genpact has been recognised as a leader in advanced analytics and insights services. 

Event highlights: 

• Keynote session with industry leaders
• Hands-on workshops and webinars
• Coding challenges and hackathons
• One-on-one coaching and mentoring activities 
• Career discussions with industry leaders
• Networking events with peers and Genpact’s hiring managers

Genpact Analytics Career Day (Online)

September 03, 2022

REGISTER NOW

What to expect: 

• Gain insights into innovative data and analytics projects and solutions 
• Connect with industry leaders in the field 
• Learn what it takes to thrive in the analytics industry 
• Meet talent acquisition managers and other key stakeholders at Genpact  

Who should attend: 

• Job seekers and those who are curious about the analytics industry and want to build a career in the field 
• Experienced professionals looking to switch jobs, including data analysts, business analysts, data scientists, data engineers, and other junior and senior-level candidates 

REGISTER NOW

About Genpact 

Genpact (NYSE: G) is a global professional services firm delivering the business outcomes that transform industries and shape the future. Fusing real-world expertise and collaborative innovation, we make businesses work better – breaking down boundaries, creating simplicity from complexity, and building ecosystems of impact. Guided by our experience reinventing and running thousands of processes for hundreds of companies, our Global Fortune 500 clients come to us for digital-led innovation and digitally-enabled operations that dig deep into data to turn insight into action. And we do it all with purpose. From New York to New Delhi and more than 30 countries in between, our 100,000+ team is passionate in our relentless pursuit of a world that works better for people. 

September 03, 2022

REGISTER NOW

What is common between Tesla, LinkedIn, and YouTube? Apart from being wildly successful companies in their own right, all three companies were created by former PayPal employees and founders. 

PayPal was originally a money-transfer service offered by Confinity, a company founded by Peter Thiel, Max Levchin, and Luke Nosek. The company was acquired by X.com in 1999, and after a few years, the latter was renamed PayPal and sold to eBay in 2002. Within four years of this transition, 12 of the first 50 employees left, however, they remained connected socially and businesswise. Over time, a number of them partnered together to form new companies and ventures. Some of these ventures became very successful and prolific. In 2007, Fortune Magazine carried an article and coined the phrase – PayPal Mafia – it was accompanied by a photo of these former PayPal employees in gangster attire. These founders are now the most influential and wealthiest people in Silicon Valley.

Cut to India, Genpact has produced some of the most influential analytics leaders that we have today. Genpact Mafia, if you will.

Yesterday’s Genpact employees, today’s analytics leaders

Bermuda-headquartered Genpact is a global professional services firm which employs over 100,000 people. It was established as a part of General Electric in 1997 before being spun off as a separate entity called GE Capital International Services (GECIS) in New Delhi. Headed by Pramod Bhasin, the company offers business process outsourcing solutions to GE’s businesses. 

Genpact is widely considered a pioneer of business process outsourcing. By 2005, GECIS became an independent company and changed its name to Genpact. Within two years, it became a publicly-traded company and since then, the company has diversified to offer AI-based services, building proprietary APIs and developing an open architecture to include all of its intellectual property and that of other providers. NV “Tiger” Tyagarajan is the current CEO and president of the company.

Genpact housed and nurtured some of the best talents in analytics who have now gone on to hold some key positions in leading organisations.

RB Rajendar, the current head of analytics – India, Citi Solutions, was one of the initial employees of GECIS. He joined the company in May 1998 as the assistant manager and was instrumental in setting up the analytics department of the company in India. He was associated with the company for over three years and rose to the position of Assistant Vice President before joining HSBC.

Rohit Tandon, the Global AI & Analytics Services Leader, Deloitte, joined GECIS in 1999 as the VP – Business Development, before diversifying into other roles within GE. He joined Genpact back again in 2006 as SVP and Business Leader- Analytics for two years. He had his third stint at the organisation in 2016 as the SVP and Analytics Business Leader, where again he spent over two years.

Between 2002 and 2010, Namit Sharma worked as the Vice President at Genpact, leading a 550-member analytics and research team working across retail banking, credit cards, auto finance, brokerage, and e-commerce. He is now the Vice President & Head of Global Delivery Center for Analytics, India at FICO.

Shuvajit Basu joined as the Delinquency & Risk Strategy Lead at GECIS in 2002. He is currently the VP and Head of Data Science at Tata Group.

Satyamoy Chatterjee, executive vice president at Analytiica Datalab, is a data science professional with an experience of 20 years. His association with Genpact dates back to 2003 when he joined the company as a Consultant after completing an MS course from Wichita State University. He worked there for three years before joining Citibank and subsequently assuming his current role at Analytiica Datalab.

As an Analytics Manager at GECIS in 2003, Arnab Chakraborty was instrumental in building the Marketing Analytics Center of Excellence (CoE) for GE Commercial Finance. He is currently the Senior Managing Director – Applied Intelligence North America Lead for Accenture AI.

Paritosh Anand is the Senior Vice President – Digital Platforms at Reliance Industries Limited, but he started his career with Genpact as a consultant in 2003.

Like Paritosh, Amit Kalra too began his professional career in 2003 with GECIS in Market Research. He is currently working with Swiss Re as Managing Director, Head Global Business Solution Centres India.

Beginning her professional career as an assistant system analyst at TCS, Mathangi Sri joined Genpact in 2005 as a consultant and worked there for over two years. Since then, Mathangi has worked in organisations like HSBC, Citibank, PhonePe, and Gojek, before joining her current company Yubi (earlier called CredAvenue) as the chief data officer.

Amit Khanna is currently a Partner at PricewaterhouseCoopers. He worked with Genpact in 2005 as the Service delivery lead ( Customer & Marketing Analytics) for over two years.

Vice President – Global Analytics at Concentrix, Hari Saravanabhavan, is an analytics leader with an experience of 25 years, working with companies like Cognizant, IBM, and Airtel. Saravanabhavan worked at Genpact between 2006 and 2008 as the assistant vice president – Retail, CPG, and Telecom analytics. At Genpact, he oversaw the deployment and delivery of analytics models and developed plans for innovative analytics interventions.

Thomas Jacob Kollenkeril joined as a consultant in 2006, rising and was the Global Operating Lead at the time of leaving the organisation in 2020. He is currently the Senior Director (Analytics) at Biocon Group.

Ram Kumar joined Genpact in 2006 as a Consultant and worked there for over two years. He rejoined the organisation in 2009 as a Manager and worked for almost seven years this time. He is now the Senior Director & Head, Data Sciences at Snapdeal.

Ishu Jain is the Head of Central Analytics at Swiggy, where she heads a team of 100 plus data scientists/analysts across central functions like delivery network optimization, customer segmentation, loyalty, traffic and acquisition. Ishu joined  Genpact as a consultant in 2006.

Training ground for future entrepreneurs

Pankaj Kulshreshtha joined GECIS as the Vice President – Analytics, in 1998. He has worked with other GE subsidiaries before coming back to Genpact as SVP & Business Leader – Analytics & Research. After a six-year stint, he went on to establish Scienaptic Systems, an AI-based Credit platform, in 2014.

Founded in 2011, BRIDGEi2i enables data-driven digital transformation for its clients, using a combination of data engineering, analytics, proprietary AI and other consulting services. In 2021, the company was acquired by Accenture. The acquisition added over 800 professionals to Accenture’s Applied Intelligence practice. Interestingly, one of the co-founders of BRIDGEi2i is Prithvijit Roy. Roy was one of the earliest employees of GECIS in 1999, where he worked as the assistant vice president, before leaving in 2005 to join HP.

Like Roy, Sayandeb Banerjee joined GECIS in 1999 as a manager. He worked at GECIS before joining GE Money in 2003. Currently, he is the co-founder and CEO of TheMathCompany, a company that helps enterprises build and maintain in-house analytics centres. He is also the co-founder/CEO of co.dx.

Sanjeev Mishra is the CEO and co-founder of Convergytics Solutions Pvt. Ltd that offers analytics solutions to Retail, CPG, Telecom, Technology & Media companies. He was associated with GECIS between 2001 and 2003.

Sarita Digumarti is the co-founder of Jigsaw Academy, an edtech firm that offers courses in AI and analytics. GECIS was one of the first organisations she worked with at the beginning of her career. In 2004, started as an assistant manager and rose through the ranks to become Assistant VP.

Apart from these, Genpact alumni have gone on to establish companies like Transitials, eWandzDigital Services, Stratbeans Consulting Private Ltd, and Stylofie, among others.

Genpact, in collaboration with Formula E team Envision Racing and MachineHack, successfully completed the Dare in Reality hackathon for data scientists and machine learning professionals on 22 November. The goal? To help the racing team improve its performance in the all-electric, international single-seater world championship. The hackathon welcomed more than 5,200 participants and over 10,000 submissions within just two weeks.

“The idea for organising the Dare in Reality hackathon was to let data science professionals, machine learning engineers, AI practitioners, and other tech enthusiasts work on a real-world problem statement,” said Krishna Rastogi, the Product Lead and Technical Architect at MachineHack. “The hackathon has had one of the highest numbers of participants and submissions at MachineHack, where the rankings were based on the RMSLE metric to predict drivers’ lap times in qualifying rounds ahead of a race. Our participants have solved the problem in many innovative ways.”

Let’s take a look at the winners who impressed the judges with their data skills and took home highly coveted cash prizes and goodies.

Rank 01: Igor Maleev

Maleev was crowned the winner of the Dare in Reality hackathon. Maleev became interested in data science while studying for a PhD in mathematics and statistics. He has experience working as a data scientist in the advertising and retail space and is a data science consultant right now.

Winning Approach

Fig 1: Data Distribution of Free Practices and Qualifying groups

Maleev says that the main idea that helped him win was to train the model on the green segment of Fig 1. After training and testing this data, he got very close to getting the score on the leaderboard during the competition. The rest was very technical and consisted of feature engineering, cleaning data, and training and tuning the model.

Check out the code here.

Rank 02: Mahesh Yadav and Vakada Naveen

Yadav became interested in machine learning when he saw intelligent virtual assistants but his full exposure came after getting into IIT Madras as a research scholar in September 2020. 

Naveen has always been fascinated by the portrayal of how AI could do wonders in futuristic movies like I, Robot. Even his final year B Tech project on machine learning was focused on this area. He has secured a place to pursue an MS through research at IIT Madras in the area of Vision and Language transformers.

Winning Approach

Yadav and Naveen followed a three-phase approach, which included:

• Data preprocessing
• Model building
• Ensembling methods

Data Preprocessing

The team preprocessed time columns by replacing them with float values, which were then separated into categorical and numerical columns. The team normalised the skewed features.  After applying one-hot encoding to handle the categorical columns and normalization on the dataset is done using MinMaxScaler. Principal Component Analysis (PCA) was performed on the dataset to reduce the dimensionality.

Model building

Yadav and Naveen tried a variety of models such as neural networks with different architectures, light gradient boosting, Xgboost, support vector regression, gradient boosting, and random forests. Neural networks performed best compared to other models. They tried hyperparameter tuning for the neural networks and found some of the best architecture to be used for ensembling. 

Ensembling Methods

Yadav and Naveen ran various neural network architectures, sampled different training datasets each time and kept track of the best models. The ensemble approaches they tried include stacking with neural networks as meta learners, stacking with machine learning models as meta learners, simple averaging, and weighted averaging. They said that the best model they submitted was from simple averaging of predictions from the best neural network models.

Check out the code here.

Rank 03: Sylas John Rathinaraj

Initially, Rathinaraj was a SAS developer and got interested in predictive analytics in 2017. He focused on learning courses in statistics, exploratory data analysis (EDA), machine learning, data science and deep learning, from Coursera and Udemy. This is the first time he has ranked in the top five in a hackathon.

Winning Approach

Here, Rathinaraj transformed all the time captured information into seconds and label encoded all the categorical features. The target variable was log-transformed to reduce skewness in the distribution. After that, the redundant features were eliminated, along with the highly correlated feature.

With that, a new feature was created, which is the time taken in all the three sectors, minus the PIT time. He created further features that show the improvement that happened in all the sectors. Along with that, Rathinaraj also created a variable from the ‘event’ column information, just taking the Free Practice and Qualifying Group, and eliminated all the numeric suffixes. He then created one additional feature as frequency encoded values for each categorical variable. 

Model Building

In this step, feature deletion, addition and selection were performed to avoid overfitting as the test data contains location 6, 7, 8 qualifying group lap alone. He evaluated the LightGBM, CatBoost and XGboost model but for final prediction, and used the CatBoost model with five-fold cross-validation. 

Talking about his experience, Rathinaraj said, “It’s been some time since I started regularly participating in MachineHack hackathons. It has been an extremely exciting journey for me and indeed very useful for my learning,” said Rathinaraj.

Check out the code here.

Rank 04: Praveen Kumar Bandla

Bandla came across the term ‘data science’ when he took a business data mining course while studying for his MBA at IIM Calcutta. He was hooked instantly by the way maths and programming can be employed to help solve complex business problems. While working at EXL, he got the opportunity to work with a US insurance client with their analytics team. He went on to pursue a PGP in data science, offered by Simplilearn in association with Purdue University and IBM. Since then, he has been participating in ML hackathons and has learnt a lot from these competitions.

Winning Approach

To start with, Bandla worked to understand the dataset and the features that were provided. He researched the context of the problem statement to get a better understanding of the task. After this, he performed EDA to explore the distribution of features and their relation to the target variable. After he figured out the features he wanted to use, he trained basic models to get an idea of where he stood on the leaderboard. 

He said, “Then, I would experiment with feature transformation, feature engineering, model tuning, boosting, stacking and so on. This would give me an idea as to how complex models are performing with the given dataset compared to simpler ones.  In this competition, I found that simpler models perform better than complex models.”

Check out the code here.

Rank 05: Mahima Arora

Arora comes with a bachelor’s degree in mathematics and a master’s in operations research. It has only been a year since Arora started working, but the experience has opened her up to different concepts, a variety of tools and a vast possibility to explore and learn more.

Winning Approach

After exploring the data, Arora started with some data cleaning that included fixing the formats of different variables and converting them into a usable form. Then, Arora performed univariate and bivariate analysis to understand the data better. In the next step, she merged weather data with the original dataset and aggregated it on the combination of location, event and source of data. With this, she calculated the mean for each of the columns and merged it with the original dataset. The imputation was carried out on columns with 60-70% missing data. 

After this, Arora converted categorical variables into dummy variables and dropped the irrelevant columns. She split the data into train and validation and started building a model using XGBoost regressor, random forest and gradient boost algorithms. She used k-fold cross-validation to tune her models and fine-tuned XGBoost Regressor with “Mean Squared Log Error” as an objective function, which gave the best performance on her validation data.

Arora’s experience at MachineHack has been enriching and fulfilling. She stated, “From cleaning the data and applying different algorithms to fine-tuning, the model has increased my overall understanding of this field. These hackathons provide a great platform to learn as well as compete in a healthy environment to improve and enhance your existing knowledge.”

Check out the code here.

Out-of-the-box solutions, high degree of skills displayed 

The Dare in Reality hackathon saw participants bring out-of-the-box solutions to the table to solve the innovative problem they’d been presented with. Having such a high level of skills on show at the Dare in Reality hackathon surely made it a huge success.

“We were amazed at the number of carefully considered solutions the hackathon received to our challenge,” said the Envision Racing team. “With the data science community demonstrating such a high level of innovation, the five winners should be particularly proud of their success. We’re already exploring how we can adapt their ideas to help the team gain an edge in qualifying.”

The Dare in Reality Hackathon 2021, powered by Genpact in partnership with Envision Racing and MachineHack, challenged participants to develop machine learning models that predict lap times in a Formula E qualifying race. The contest  closed on 22 November having received a record number of entries.

Within two weeks, the hackathon received more than 5,200 participants and 10,000+ submissions. Currently, a panel of judges are selecting the winners. Interestingly, the level of competitiveness in the final score is also marginally high (i.e. close to 0.01 to 0.001 difference) in the leaderboard ranking.

Also, the hackathon had one of the highest prize amounts compared to any other hackathons hosted previously. The ‘Dare In Reality’ was indeed a first-of-its-kind hackathon ever hosted globally. 

Moreover, hackathon entrants showcased their advanced data analytics and AI skills, creating machine learning models to help the Formula E team predict lap times in the important qualifying sessions that determine where on the grid each driver starts a race. 

The hackathon winners will receive a range of cash and tech prizes, including: 

• First prize: $7,000 
• Second prize: $5,000 
• Third prize: $3,000 
• Fourth prize: iPad Air 128 GB 
• Fifth prize: Apple AirPods

What Did You Miss? 

Touted as the largest machine learning hackathon globally, ‘Dare In Reality’ gave participants a unique opportunity to work on one of the most complex datasets out there, curated by Envision Racing and Genpact. 

The hackathon was the first time Genpact and Envision Racing gave people outside the partnership the opportunity to help the team make even better use of its data and analytics. 

The hackathon welcomed participants from all across the globe, including the US, China, Russia, Germany, Vietnam, India and South Korea. The entrants also got to compete with experienced professionals. Some of them were leaders in the data science industry with titles like the head of analytics, CTO, and senior data analysts. 

Besides experienced professionals, the hackathon also saw participation from various premium institutions like IITs, IIMs, NITs and others. 

Formula E is the world’s first all-electric international single-seater championship. The race consists of 12 teams and 24 drivers. In every race, drivers and their engineers need to make rapid decisions on how to use their energy, overtake or defend, respond to competitors, and more. To help Envision Racing make the right decisions on the racetrack and beyond, Genpact’s data science and machine learning experts use sophisticated algorithms to provide the team’s drivers and engineers with invaluable insights they need to improve their competitive edge. 

The hackathon presented participants with the challenge of predicting what drivers’ lap times would be in the all-important qualifying sessions. Ahead of every race, drivers compete to establish their place on the starting grid. Being able to anticipate the lap times for each driver based on the conditions of the track, weather, driver’s experience and other critical and evolving factors offers an invaluable advantage. Our hackathon entrants put data and analytics to work to address this challenge. 

We will announce the names of all the winners of the Dare In Reality Hackathon 2021 shortly, alongside details of the winning approach and solutions.  

If you missed this hackathon, don’t worry. We’ll have more that you can sign up for next year.

Praxis Business School recently announced their placement stats for the Praxis Post Graduate Program in Data Science. The institute said in a social media post that the campus placements for the Praxis Post Graduate Program in Data Science (PGPDS) reached 50 percent within just three months of the course commencement. 

The recruiting partners include names like Accenture, Genpact, LatentView Analytics, Subex, L&T Financial Services, HSBC, PwC, Poonawalla Fincorp, Alumnus Software Limited.

Praxis is a premier Business School with campuses in Kolkata and Bangalore. Praxis pioneered the teaching of analytics as a discipline by launching a full-time program in Business Analytics from its campus in Kolkata in 2011.

Praxis offers a nine-month full-time Postgraduate Programme in Data Science. Candidates applying for this course are usually people already in the workforce who quit their lucrative jobs to take the data science route. 

In Formula E – the first all-electric, single-seater world championship – even the most subtle performance improvements can lead to victory. These could be changes to not only the car, but also how the team uses data and analytics to improve energy management, race strategy, or competitive advantage to shape a race’s outcome.

That is why Envision Racing – a founding Formula E team – uses advanced data analytics and artificial intelligence (AI) to stay ahead of the pack. Business transformation firm Genpact is partnering with the team to help bring this extra edge to Envision Virgin’s performance.

And now, Genpact is giving data scientists outside the partnership the opportunity to help the Formula E team win on the racetrack. Together with Envision Racing and MachineHack, Genpact launched ‘Dare in Reality,’ a data science and machine learning hackathon that promotes the use of advanced data analytics and AI to predict lap times in qualifying races. 

Register here for hackathon

How Genpact Is Giving Envision Racing A Boost

Formula E racing has 12 teams and 24 drivers – all driving battery-powered cars. In every race, drivers and their engineers need to make rapid decisions on how to use their energy, when to overtake or defend, how to respond to competitors, when to take attack mode (and an extra boost of energy available to all drivers), and much more. 

Thanks to Genpact’s data science and machine learning capabilities, Envision Racing can combine the talent of its drivers and engineers with fast access to insights from sophisticated algorithms to give the team an extra edge to win. 

The Genpact team provides insights that help drivers prepare for each race by analysing their performance in previous contests and practice runs in the simulator. They can also make predictions on how many laps a race will be and help the team understand what other drivers may be planning by tapping into race-day radio communications. 

Similarly, technology enables the team to easily report its carbon emissions to The Carbon Trust to remain the greenest team on the greenest grid. And finally, analytics also helps identify fan personas, enabling the team to build its base of socially conscious supporters. 

And now the Dare in Reality hackathon gives you a unique opportunity to help the team make even better use of data and analytics.   

What are you waiting for? Unleash your data analytics skills today, participate in this prestigious hackathon, and collaborate with the most innovative minds in the industry. But hurry, it closes in 8 days!

Register here for hackathon

This hackathon is a two-week event where data science and machine learning professionals get a chance to win exciting merchandise and cash prizes totalling INR 12 lakhs (about $16,000).

For more details click here. 

Genpact, in collaboration with Envision Racing and MachineHack, is launching a hackathon for data scientists and machine learning professionals called ‘Dare in Reality,’ from November 8 onwards. The hackathon winner will get a chance to win exciting cash prizes and goodies. 

Genpact is a global professional services firm that makes business transformation real. With a team of 90,000+ employees, Genpact serves more than 800 clients across 70+ countries. Forbes recently called Genpact out in its list of World’s Best Employers 2021. 

With this machine learning hackathon, Genpact aims to see how participants can help the Formula E team improve its performance on the racetrack in the all-electric, international single-seater world championship. 

The partnership between Genpact and Envision Racing uses data, innovation, real-time insights, and process excellence to achieve three core goals: boosting the team’s racing performance, climate change, and building and energizing a passionate, socially conscious fan base.

Ready, Steady, Go! 

The two-week Dare in Reality Hackathon 2021 is for data science professionals, machine learning engineers, artificial intelligence practitioners, and other tech enthusiasts to showcase their skills and impress the judges. The winners are rewarded with cash prizes.

The challenge starts on November 8, 2021

The Challenge is on…

Besides disrupting motor racing and growing a diverse and global following, Formula E also fights climate change. It is creating a technical and sustainable development testbed that helps countries address mobility and environmental issues. 

In each race, 12 teams – each with two drivers – compete in electric, battery-powered cars. Every team is focused on securing the best competitive advantage to cross the finish line first. 

Formula E cars have evolved through years of research. And for a team to win, it needs a combination of driver skill and data analytics. But, Several factors affect their performance during a session, including: 

• Weather
• Rain 
• Wind
• Track temperature 
• Ambient temperature  
• Track evolution: The way the track changes during and between sessions. As the cars leave rubber and debris on the tracks and weather affects the conditions of the driving environment – ambient temperature, humidity, rainfall, etc. – the track evolves and the time taken to complete a lap changes (increases or decreases based on positive or negative track evolution). 
• Driver’s familiarity with the track

So, in this hackathon, participants should use machine learning to predict lap times for a specific Formula E session – the qualifying session that determines where each car will be positioned at the start of the race.  

Submission Guidelines 

Sklearn models support the predict() method to generate the predicted values.

You should submit a .csv file with exactly 1957 rows with 1 column(LAP_TIME). Your submission will return an Invalid Score if you have extra columns or rows. The file should have exactly 1 column.

Note: Do not shuffle the sequence of the test series

For participants using Pandas: 

submission_df.to_csv(‘my_submission_file.csv’, index=False)

Evaluation Criteria:

​​The submission will be evaluated using the RMSLE metric. Participants can use np.sqrt(mean_squared_log_error(actual, predicted)) to calculate the same

• This hackathon supports private and public leaderboards
• The public leaderboard is evaluated on 30% of Test data
• The private leaderboard will be made available at the end of the hackathon, which will be evaluated on 100% of Test data
• The Final Score represents the score achieved based on the Best Score on the public leaderboard

Prizes: 

• First Prize: $7000
• Second Prize: $5000
• Third Prize: $300
• Fourth Prize: iPad Air 128 GB
• Fifth Prize: Apple AirPods 

The challenge ends on November 22, 2021

Dataset Description:

• Train.csv – 10276 rows x 25 columns (includes target column as LAP_TIME)
• Test.csv – 420 rows x 25 columns
• Sample Submission.csv — Please check the “Evaluation” section on MachineHack Page for more details on generating a valid submission.

Attribute Description:

• Number
• Driver number
• Lap number
• Lap time
• Lap improvement
• Crossing finish line in pit
• Session 1 (S1)
• S1 improvement
• Session 2 (S2)
• S2 improvement
• Session 3 (S3)
• S3 improvement
• Kph
• Driver name
• Pit time
• Class
• Qualifying group
• Team
• Manufacturer
• Power
• Location
• Event

Input data:

• Data from the practice and qualifying sessions
• Data tables:
  • Timing Data: The standings for each driver in a race, lap-by-lap data for each driver for free practice (FP) 1, free practice (FP) 2 and qualifying session (Q)
  • Weather: how weather conditions changed during a session

Output:

• Provided data for FP1 and FP2 to build a model to predict the lap times for qualifying sessions
• For the test data, we will provide FP1, FP2 data (timing data and weather). Predict the lap times for qualifying sessions

Skills: 

• Multivariate Regression
• Big dataset, underfitting vs overfitting
• Optimizing RMSLE to generalize well on unseen data

Other details: 

Situation and Race Conditions

• All participants have the same car and battery/power to consume during the session
• The race runs for 45 mins (fixed) plus one additional lap
• The driver who crosses the finish line first wins the race
• If there are crashes or problems on race day, the safety car enters the track until everything is safe. All drivers must stay behind the safety car, stay below 50kph, and cannot overtake
• If the safety car comes on, there will be fewer laps as the race time is fixed
• For practice sessions, each driver can complete one lap in 250 kW, one lap in 235 kW and all remaining laps in 200 kW
• For qualifying sessions, each driver can complete a maximum of 3 laps, where only one lap can be in 250 kW, and all others need to be 200 kW
• For race sessions, laps are energy limited, as opposed to power limited
• In practice sessions, when drivers complete multiple adjacent laps with similar lap times, they generally practice race laps and, therefore, energy-limited laps
• Standard session durations are as follows:
  •  FP1: 45 minutes
  •  FP2: 30 minutes
  •  Q1 to Q4: 4 minutes per group
  •  Super pole: 20 minutes maximum
  •  Race: 45 minutes plus one lap

Suggested Approach:

• Data Preparation: Build a master data frame combining tables from different sessions, drivers, qualifying, and practice races. Join with weather data to get the final data set
• Explore data to understand the significant variables and generate derived variables if needed
• Build a model to predict the lap times for each qualifying lap using the provided test data for a session

Championship Basic structure

• Twenty-four drivers (two per team) compete in each Formula E race
• Each driver ranks separately, but their total scores give the overall team ranking
• There are 12 races in a season held over 8 months
• There are 2 free practice sessions before a race  
• After the practice sessions, qualifying sessions run for a very limited number of laps to decide the pole position (who starts in the first row and then the following positions). A super pole can follow multiple qualifying sessions to decide the driver standings at the race start
• The race runs for 45 minutes plus one lap

Start Date: Nov 8, 2021

End Date: Nov 22, 2021

In the heat of a Formula E race, teams need fast access to insights that can help drivers make split-second decisions and cross the finish line first. Can your data-science skills help Envision Racing, one of the founding teams in the championship, take home even more trophies?

To do so, you will have to build a machine learning model that predicts the Envision Racing drivers’ lap times for the all-important qualifying sessions that determine what position they start the race in. Winning races involve a combination of both a driver’s skills and data analytics. To help the team you’ll need to consider several factors that affect performance during a session, including weather, track conditions, and a driver’s familiarity with the track. 

Genpact, a leading professional services firm that focuses on digital transformation, is collaborating with Envision Racing, a Formula E racing team and digital hackathon platform MachineHack, a brainchild of Analytics India Magazine, is launching ‘Dare in Reality’.’ This two-week hackathon allows data science professionals, machine learning engineers, artificial intelligence practitioners, and other tech enthusiasts to showcase their skills, impress the judges, and stand a chance to win exciting cash prizes.

The FIA Formula E World Championship is the first fully electric international single-seater street racing series. Envision Racing uses digital technologies and human-centred design to stay ahead. As Envision Racing’s partner, Genpact uses data to deliver insights that help the team reach the podium and fulfil its purpose: to win the race against climate change.

Genpact Partners with the team to achieve three core goals: boosting the team’s racing performance, tackling the world’s biggest environmental challenge, and building and energizing a passionate, socially conscious fan base.

Starting on 8 November, the Dare in Reality Hackathon 2021 gives data professionals an exciting opportunity to prove their capabilities by pushing the envelope on innovation, technical prowess, and creativity. The participants will also stand a chance to win incredible cash prizes.

What are you waiting for? Sign up for an unforgettable experience, collaborating with some of the most innovative minds.

Show Genpact and Envision Racing how your data science skills can give the team an extra edge. 

Register here. 

Update: November 3, 2021 11:35 | ‘Envision Virgin Racing’ has been replaced with ‘Envision Racing,’ to represent its full ownership by Envision Group.

Sreekanth heads the AI/ML practice for Genpact Analytics and drives global AI/ML projects delivery. He brings over two decades of innovation and industry expertise to his role, leading strategy, business transformation, product development, and delivering high-end analytical solutions. Sreekanth has incubated and launched over 50 advanced analytics solutions in the global market. He has worked closely with Fortune 500 clients to drive impact on their business by enabling innovative AI-led solutions and practices. 

His primary focus is competency building in AI ecosystems such as Machine Learning, NLP/Text Mining, Computer Vision, and nurturing new capabilities. In addition, he develops, mentors and guides a global team to deliver complex AI/ML Models and capabilities at scale while promoting engagement and employee growth. 

Before Genpact, Sreekanth assumed end-to-end responsibility of developing analytics engines, setting up virtual captive teams and building Big Data Analytics platforms. Sreekanth also led a large Analytics team at Symphony Marketing Solutions. Here, he focused on building a Digital Retail Measurement system with Advanced embedded algorithms to solve multiple business problems of Fortune 500 CPG Retail clients. He joined Genpact in February 2010 as part of Genpact’s acquisition of Symphony Marketing Services. 

His career commenced in the world of consumer research/survey research at Kantar group, building advanced statistical models to solve complex challenges like measuring advertising effectiveness, predicting customer satisfaction etc. 

Sreekanth holds a Postgraduate Degree in Marketing from XLRI Jamshedpur and a bachelor’s in computer science.

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