Vice President - Model Validation/Credit Risk Models

Description:

- Manage end-to-end validation of CCR models, including Monte Carlo exposure simulation engines, netting and collateral models, CVA/XVA pricing engines.

- Challenge modelling assumptions, mathematical frameworks, calibration, and stress testing approaches.

- Review model documentation, coding standards, and implementation testing (including independent replication or benchmarking as needed

- Basic understanding of stochastic calculus, numerical techniques for derivatives pricing (Monte Carlo / Finite Difference) and comfort level with one / more programming languages is expected

Expertise in at least one of the following areas:

- Risk Models: Counterparty Risk Exposure models

- Credit Models: CVA calculation

- A strong graduate/ post graduate degree in Engineering, Mathematics, Computer Science, Economics or other quantitative area

- Proven work experience conducting quantitative analysis using programming (proficiency in Python, R, or VBA is required).

- You will lead the independent validation of complex models used to measure CCR exposure such as PFE, EPE, EAD and CVA. You will drive the evaluation of both internal risk management models and regulatory capital models, ensuring they are conceptually sound, accurately implemented, and compliant with global regulatory standards (e.g., Basel III, CRD IV, PRA SS 1/23).

- This is a high-visibility role with significant interaction across model development, risk management, front office, audit, and regulatory stakeholders

Stakeholder Engagement:

- Communicate validation findings to model owners, governance committees, and senior management.

- Influence model risk policy and contribute to model governance frameworks.

Documentation and Governance:

- Deliver high-quality model validation reports and executive summaries aligned with internal policy and regulatory guidance (e.g., Basel III, CRD IV, PRA SS 1/23).

- Ensure models are appropriately categorized and inventoried within the bank's Model Risk Management framework.