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Job Description & How to Apply Below
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 m 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 and on Linked In, X, You Tube, and Facebook.
Inviting applications for the role of Director Risk Management (Analytics and Modeling)
As a Director, Risk Analytics and Modeling, in our Financial Services Risk Practice, you will lead solution development, client advisory, and strategic transformation programs across risk analytics, quantitative modeling, and model lifecycle management for global banks and financial institutions.
The role combines deep expertise in risk modeling, regulatory frameworks, and advanced analytics with strong consulting and commercial capabilities to design and deliver data-driven, analytics-led, and AI-enabled solutions. The successful candidate will play a key role in expanding our risk analytics and modeling capabilities globally.
Key Responsibilities:
Risk Analytics & Modeling Transformation
• Lead transformation initiatives across risk analytics and model lifecycle functions, including model development, validation, monitoring, and implementation
• Design target operating models and model lifecycle frameworks aligned with regulatory expectations (e.g., SR 11-7, ECB/PRA guidelines)
• Develop and deliver solutions across stress testing, capital planning, portfolio analytics, and regulatory modeling frameworks
• Enable modernization of risk analytics capabilities through advanced analytics, automation, and scalable model deployment frameworks Client & Solution Leadership
• Lead solution design and proposals for complex risk analytics and modeling transformation engagements
• Shape and lead multi-year enterprise analytics and model transformation programs
• Build relationships with CROs, Heads of Model Risk, and Risk Analytics leadership
• Lead client workshops and executive discussions on quantitative risk, model governance, and analytics transformation
• Partner with data, technology, and AI/analytics teams to deliver scalable and robust risk analytics solutions Risk Modeling, Analytics & AI-Driven Solutions
• 10–15 years of experience in risk analytics, quantitative modeling, or model risk management within banking or financial service
s
• Master’s degree (or higher) in Finance, Mathematics, Statistics, Economics, or related quantitative field
• Strong experience working with global banks/financial institutions and/or leading consulting firms
• Deep expertise in end-to-end model lifecycle management, including model development, validation, governance, and deployment
• Strong understanding of regulatory frameworks such as SR 11-7, Basel III/IV, CCAR/DFAST, IFRS9/CECL, FRTB, and IRB frameworks
• Hands-on experience across credit, market, or enterprise risk models
• Certifications such as FRM, CFA preferred
• Experience with risk analytics and modeling ecosystems, including:
o Programming and analytics tools (Python, SAS, SQL, or similar)
o Advanced statistical and machine learning techniques (regression, time series, survival models, tree-based methods, neural networks)
o Modern data platforms (Snowflake, Databricks) and cloud ecosystems (AWS, Azure, GCP)
o Model lifecycle tools, governance platforms, and analytics environments
o Data…
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