Senior Vice President - Quant Credit Risk Analytics

Experience:

- 15+ years of experience in credit risk management, risk analytics or related quantitative Finance Fields, with a track record of increasing responsibility.

- Significant people management experience is required { you should have successfully led high-performing teams and managed multi-disciplinary projects.

- Experience in a global Financial institution or credit rating agency, particularly in roles involving credit risk modeling or analytics, is highly desirable.

Technical Expertise:

- Deep understanding of credit risk modelling and quantitative techniques.

- Expert knowledge of probability of default (PD), loss given default (LGD), and exposure at default (EAD) modeling, credit scoring methodologies, and portfolio credit risk concepts.

- Familiarity with counterparty credit risk metrics (e.g., PFE, CVA) and structured credit products is a plus.

- Strong foundation in statistics, econometrics, and data analysis; proficiency in programming (Python, R or similar) for risk analytics is preferred.

- Ability to oversee the development of models employing techniques ranging from logistic regression to advanced machine learning, while ensuring they are conceptually sound and fit for purpose.

- Oversee the implementation of frameworks such as Basel III Internal Ratings-Based approaches and stress testing programs (e.g., CCAR). Engage with regulators and internal Model Risk Management on model approvals, validation exercises, and regulatory examinations.

Education:

- Advanced degree (Master's or PhD) in a quantitative discipline such as Finance, Economics, Statistics, Mathematics, Engineering, or a related Field.

- A strong academic foundation in quantitative methods and risk management principles is essential.