Credit Risk Model Developer

A Leading Banking & Financial Services Group is seeking a quantitative Credit Risk Model Developer at the Manager or Senior Manager level to build advanced credit risk models across India. In this core statistical modeling role, you will take full responsibility for designing, developing, and validating behavioral and collection scorecards to assess borrower risk. Furthermore, you will build and calibrate models aligned with IFRS 9 Expected Credit Loss (ECL) frameworks and Internal Ratings-Based (IRB) approaches for regulatory capital. Consequently, this position is crucial for optimizing credit underwriting and capital efficiency.

The Credit Risk Model Developer must combine strong econometric and statistical theory with advanced programming proficiency in SAS, R, Python, and SQL. Working closely with risk governance, finance, and regulatory teams, you will perform back-testing, benchmarking, stress testing, and scenario analysis across retail and corporate portfolios. Therefore, the group is looking for an analytical specialist who interprets complex regulatory guidelines and builds robust risk analytics seamlessly. If you want to develop frontier quantitative risk models, this position offers an ideal path.

Key Responsibilities

• Design, calibrate, and validate quantitative behavioral, application, and collection scorecards across loan portfolios.
• Develop, maintain, and enhance statistical models aligned with IFRS 9 standards for Expected Credit Loss (ECL) estimation.
• Build Internal Ratings-Based (IRB) models (PD, LGD, EAD) for regulatory capital calculation under Basel frameworks.
• Execute rigorous model validation routines, including back-testing, sensitivity analysis, benchmarking, and stability monitoring.
• Perform portfolio-level stress testing, macroeconomic scenario simulations, and risk-based segmentation analysis.
• Collaborate with risk governance, IT, and regulatory compliance teams to document and deploy model engines.
• Produce comprehensive model documentation, technical methodology papers, and validation decks for regulatory review.

Requirements and Qualifications

• Postgraduate degree in Statistics, Economics, Mathematics, Econometrics, Finance, or an allied quantitative branch.
• 6+ Years of proven professional experience in quantitative credit risk model development and statistical modeling.
• Deep hands-on expertise with scorecard development, IFRS 9 ECL methodologies, and Basel IRB frameworks.
• Advanced programming proficiency using statistical data tools including SAS, Python, R, and relational SQL.
• Beneficial credentials: FRM, CFA, or PRM certifications; experience in Indian banking or global financial institutions.