AI Led Credit Risk Modelling - Manager

About the role

We are looking for a Manager – Credit Risk Modelling with strong expertise in credit risk analytics, bureau data analysis, and model development. The role involves leading the development, validation, and enhancement of credit risk models to support lending decisions, portfolio monitoring, and risk strategy. The candidate will work closely with risk, policy, underwriting, and business teams to translate analytical insights into effective credit risk strategies and ensure robust model governance.

Key Responsibilities

• Lead the development, enhancement, and maintenance of credit risk models, including application scorecards, behavioral scorecards, and risk segmentation models.
• Perform advanced data analysis using internal datasets and external bureau data (CIBIL, Experian, Equifax, CRIF) to derive actionable risk insights.
• Develop and implement models using statistical techniques such as logistic regression, decision trees, and machine learning methods where applicable.
  
• Drive model validation, monitoring, and performance tracking, including stability analysis (PSI, CSI), model recalibration, and benchmarking.
• Partner with business, policy, and underwriting teams to translate model outputs into risk strategies, credit policies, and portfolio management actions.
• Lead portfolio risk analytics, segmentation analysis, and loss forecasting initiatives to support risk management decisions.
• Prepare and maintain comprehensive model documentation in line with internal governance frameworks and regulatory requirements.
• Ensure compliance with internal risk policies and regulatory guidelines related to credit risk modelling and model governance.
• Support senior leadership with risk insights, reporting, and strategic recommendations for improving credit risk performance.
• Mentor junior analysts and contribute to building strong analytics capabilities within the team.

Preferred Qualifications

• 4+ years of experience in credit risk modelling, analytics, or risk strategy in NBFCs, banks, fintech, or financial services.
• Strong experience working with credit bureau data (CIBIL, Experian, Equifax, CRIF).
• Proficiency in Python, SAS, R, SQL, or similar analytical tools.
• Hands-on experience with scorecard development, model monitoring, and risk analytics frameworks.
• Strong analytical thinking, stakeholder management, and problem-solving skills.