AVP, Lead Data Science Professional

Ready to shape the future of work?

At Genpact, we don’t just adapt to change—we drive it. AI and digital innovation are redefining industries, and we’re leading the charge. Genpact’s AI Gigafactory , our industry-first accelerator, is an example of how we’re scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI , our breakthrough solutions tackle companies’ most complex challenges.

If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that’s shaping the future, this is your moment.

Genpact (NYSE : G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions – we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.Com and on LinkedIn , X , YouTube , and Facebook .

Inviting applications for the role of Assistant Vice President – Lead Data Scientist .

In this role, ML / DL / GenAI is critical to harness advanced analytics and AI for strategic advantage. The role drives predictive and generative modeling, optimizes decision-making, and ensures scalable, ethical AI adoption across functions. By leading teams and aligning models with business goals, the position maximizes ROI from data investments. Apply advanced statistical modeling and predictive analytics in collaboration with HR domain experts to design AI / ML-driven workforce analytics solutions. Focus on employee experience, talent optimization, and workforce planning through methods such as regression analysis, classification, clustering, and time-series forecasting, ensuring data-driven decision-making across HR functions.” This role enables enhanced demand forecasting, workforce analytics, strengthening competitiveness in the dynamic consumer goods industry.

Responsibilities

• ML / DL - Demonstrate deep expertise in statistical and machine learning techniques, including regression, classification, natural language processing (NLP), and advanced modeling approaches, to deliver business-impactful AI solutions.
• Model Development & Deployment – Lead end-to-end ML, Deep Learning, and GenAI solution development, from problem definition to scalable production deployment.
• AI / ML Pipelines – Architect and operationalize advanced pipelines, including RAG frameworks with LangChain, LangGraph, and vector databases, embedded into GenAI / Agentic AI applications.
• Business Integration – Drive incorporation of AI-powered insights into enterprise dashboards and decision systems to enable data-driven strategies.
• Leadership & Governance – Provide technical leadership, mentorship, and governance, setting standards for model development, experimentation, and data pipelines.
• Cross-Functional Alignment – Collaborate with engineering, product, HR, and business stakeholders to align AI initiatives with enterprise goals and workforce analytics.
• Generative AI & LLMs – Leverage frameworks such as OpenAI, Azure OpenAI, and Hugging Face to accelerate automation and augment cognitive intelligence.
• Scalability & Monitoring – Ensure scalability, interpretability, monitoring, and continuous optimization of deployed models across cloud platforms (AWS / GCP / Azure).
• Conduct training - Develop and deliver structured training programs to upskill business users, data scientists, and cross-functional teams on ML / DL / GenAI concepts, tools, and applications. This includes creating hands-on workshops, knowledge-sharing sessions, and onboarding material to ensure smooth adoption of AI-driven systems.
• Communication changes - Establish clear communication frameworks to articulate the value, impact, and progress of AI initiatives. This involves crafting stakeholder-focused messaging, addressing concerns about technology adoption, and ensuring transparency around model usage, data governance, and organizational benefits.
• Drive change management - Lead organizational transformation by embedding AI into workflows through structured change management strategies. Align stakeholders, set adoption KPIs, manage resistance, and ensure smooth cultural and operational integration of AI. This includes building executive sponsorship, feedback loops, and long-term adoption roadmaps.
• Collaborative Execution - Partners with cross-functional teams (engineering, product, HR, and business units) to translate strategic objectives into actionable AI / ML initiatives, ensuring alignment between technical solutions and business needs.
• Leadership and Mentorship - Guides the data science team through model development, deployment, and monitoring, setting technical standards, reviewing work, and fostering continuous skill development.
• Stakeholder Engagement - Acts as a bridge between technical teams and business leaders by communicating progress, demonstrating AI-driven impact, and driving adoption through change management and structured engagement.

Qualifications We Seek in You!

Minimum Qualifications / Skills

Preferred Qualifications / Skills

Why join Genpact?

Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters : Up.

Let’s build tomorrow together.

Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military / veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation.

Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.