Director – Risk Analytics & Modeling and Transformation

As an AVP (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 services
• 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 visualization tools (Power BI, Tableau, or similar)
• Experience applying advanced analytics, AI/ML, and automation to model lifecycle and
risk management is highly desirable

Skills
Python, AWS, Azure, GCP, SQL, Snowflake, Databricks, Machine Learning, Power BI, Tableau

Work arrangement
Hybrid