Manager | Model Validation Quant - CCR | Hyderabad | Regulatory & Financial Risk

The Team

Deloitte Strategy, Risk & Transaction helps entities mitigate risk while discovering new opportunities to create value. Our end-to-end risk services span all domains, from managing strategic risks in the C-Suite to improving board oversight, and from balancing financial and environmental policies to addressing cyber threats. Learn more about Risk, Regulatory & Forensic)

Your work profile

•  We are seeking a Market Risk Quant to support model development and validation. The role involves developing, reviewing/validating Market Risk (FRTB IMA, SA and Basel 2.5), Counterparty Credit Risk and Pricing models. Candidate must have relevant experience in statistical modelling, quantitative research, stochastic calculus, market risk management, FRTB or any other related field.
• Conducting independent reviews and validation of: Market Risk Models (FRTB – IMA & SA, Basel 2.5, VaR, Expected Shortfall, Sensitivities)
• Counterparty Credit Risk Models, including IMM / internal exposure models (EPE, EE, PFE), XVA models, Margin models (DIM, SIMM)
• Stress Testing Models (CCAR, DFAST, ICAAP)
• Assess model inputs, outputs, and assumptions; evaluate conceptual soundness and methodological appropriateness
• Perform performance testing, benchmarking, sensitivity analysis, and back-testing
• Review model implementation and identify potential model risks and remediation actions
• Prepare and review comprehensive validation and model risk reports aligned with regulatory expectations (e.g., SR 11-7, ECB, PRA)

Key skills required: 

• Master’s degree in quantitative finance, Financial Mathematics, Statistics, Economics, Engineering, MBA or a related field
• 5-8 Years of relevant experience
• Others - Certifications: FRM, CFA, CQF are a plus
• The candidates will be required to have sound knowledge and close to 2-7 years of experience in either of the areas below. Market Risk models: VaR / RNIV models, IRC, SA-CVA, FRTB models: SA, IMA
• Stress testing and Capital models: CCAR, DFAST, ICAAP
• CCR: SACCR, XVA models, Risk factor simulation models, margin models like IM, VM, SIMM, Exposure models
• The candidate should have strong understanding of: Market Risk metrics (VaR, Expected Shortfall, sensitivities, FRTB, back-testing)
• CCR metrics (EPE, EE, PFE, EAD, SA-CCR, margin models)
• Stochastic calculus, probability theory, change of measure, numerical methods Statistical techniques and tests (ADF, KPSS, Durbin-Watson, etc.)
• Stress testing, scenario analysis, and risk management strategies
• Derivatives and financial instruments across equities, fixed income, FX, and commodities Strategy