Responsibilities
- Design, develop, and validate risk models (scorecards, look-alike models, behavioural risk models) to optimize credit decisioning.
- Conduct portfolio analytics to monitor delinquency trends, vintage analysis, and risk-return trade-offs.
- Leverage statistical and machine learning techniques to improve customer underwriting, fraud detection, and collection strategies.
- Work closely with credit, product, and technology teams to implement and refine data-driven risk policies.
- Identify early warning signals and recommend changes in credit approval criteria.
- Perform A/B testing and back-testing of models to ensure robustness and accuracy.
- Partner with credit bureaus, data providers, and internal teams to source and integrate new data variables.
- Create dashboards, MIS, and insights for leadership to enable risk-based decision-making.
- Accustomed to dealing with ambiguity in a fast-paced environment.
- Proven ability to collaborate successfully across cross-functional teams.
Requirements
- 3+ years of experience in risk analytics within an NBFC, fintech.
- Strong exposure to AI/ML, credit risk modelling, portfolio analytics, and policy formulation.
- Hands-on experience with look-alike models, scorecards, and data modelling techniques.
- Proficiency in SQL, Python /R, and statistical modelling techniques.
- Understanding of credit bureau data (CIBIL, Experian, Equifax, CRIF) and alternate data usage.
- Strong analytical, problem-solving, and communication skills.
- Educational background in Statistics, Mathematics, Economics, Engineering, or related fields (Tier-1/Tier-2 institute preferred).
This job was posted by Anchal Saini from ZET.
