Key Responsibilities :

1) Develop, validate, and monitor credit risk models for retail/commercial portfolios.

2) Perform model implementation, back-testing, and performance tracking.

3) Analyze large datasets using SQL (complex queries) and SAS (Basic & Advanced).

4) Build and automate analytical solutions using Python and programming logic.

5) Conduct model validation as per regulatory and business standards.

6) Work closely with risk strategy, data science, and business teams to provide insights.

7) Prepare documentation, model reports, and risk assessment summaries.

8) Support regulatory audits and model review processes (e.g., IFRS9, Basel norms).

9) Ensure accuracy, robustness, and compliance of credit risk models

Required Skills & Expertise :

1) SAS (Base & Advanced) - Data manipulation, analytics, statistical procedures.

2) SQL (Complex queries) - Joins, subqueries, CTEs, performance optimization.

3) Python Programming - Data handling, model development, automation scripts.

4) Credit Risk Modelling - Scorecards, PD/LGD/EAD modeling, validation.

5) Understanding of statistical techniques - Regression, time-series, clustering, etc.

6) Experience with model documentation and regulatory compliance.

Preferred Qualifications :

- Bachelors or Masters degree in relevant fields.

- 2 to 7+ years of experience in credit risk analytics or model development.

- Exposure to BFSI / Banking / Financial Services domain.