Assistant Vice President - Counterparty Credit Risk Quantitative Analyst - Risk Analytics & Model Development Team

Description:

Job Title: AVP QA CCR (Counterparty Credit Risk)

Location: Mumbai

Experience: 4 to 14 years

Open Positions: 4

Job Description:

We are seeking an AVP Counterparty Credit Risk (CCR) Quantitative Analyst to join our Risk Analytics and Model Development team.

The ideal candidate will have strong quantitative and coding skills, deep knowledge of credit and market risk models, and hands-on experience with Python or C++.

This is a high-impact role that involves developing, validating, and implementing CCR models aligned with regulatory frameworks such as Basel III/IV, SR 11/7, SS1/23, and SS12/13.

Key Responsibilities:

- Develop, enhance, and validate Counterparty Credit Risk (CCR) models, including IMM, SA-CCR, CVA, PFE, EPE, EEPE.

- Perform back-testing, benchmarking, and numerical analysis of models.

- Work on Monte Carlo simulations, exposure and collateral modelling, and risk factor modelling across multiple asset classes (Interest Rates, Equities, Credit, Commodities).

- Collaborate with Model Owners, Audit, and Validation teams to ensure compliance with internal and external regulatory standards.

- Contribute to stress testing, scenario analysis, and model performance reviews.

Required Skills:

- Strong understanding of CCR concepts: IMM Models, SA-CCR, CVA, Basel Framework, Monte Carlo Simulation, Exposure/Collateral Modelling, Derivatives Pricing, Greeks, Risk Factor Modelling.

- Expertise in Back-testing, Numerical Analysis, and regulatory frameworks like SR 11/7, SS1/23, SS12/13.

- Hands-on programming experience in Python or C++ (mandatory).

- Experience in Model Development and/or Model Validation (core development preferred).

- Exposure to Stress Testing / Scenario Modelling / Statistical Modelling for wholesale credit portfolios.

- Understanding of Basel III/IV regulatory requirements and FRTB framework.

Qualification:

- Postgraduate degree in Quantitative Finance, Mathematics, Statistics, Engineering, or related fields.