Position Overview:
We are looking for a Data Scientist with deep expertise in credit risk model development to join our data analytics team. This role is responsible for building, validating, and enhancing models that drive credit decisioning and portfolio risk management. The successful candidate will combine advanced modeling skills with strong business understanding to deliver models that are both statistically robust and practically applicable in lending operations.
Key responsibilities:
- Design, develop, and implement credit risk models (e.g., application scorecards, behavioral models, PD/LGD/EAD models) using advanced statistical and machine learning techniques.
- Conduct model validation, back-testing, and stress testing to ensure accuracy, stability, and compliance with regulatory requirements.
- Partner with credit risk, collections, and product teams to ensure models are aligned with business strategy and operational needs.
- Document model development methodology, assumptions, and performance monitoring in line with model governance and regulatory standards.
- Monitor and recalibrate models to ensure continued predictive accuracy and relevance over time.
- Provide technical guidance and mentor junior analysts/data scientists on modeling best practices.
Qualifications:
- Bachelor's or Master's degree in Statistics, Mathematics, Data Science, Economics, or related field.
- 3+ years of hands-on experience in credit risk model development within a financial institution, fintech, or consulting environment.
- Strong expertise in statistical modeling techniques (e.g., logistic regression, survival analysis, decision trees, machine learning methods).
- Proficiency in Python for model development; strong SQL for data extraction and preparation.
- Solid understanding of the credit lifecycle (underwriting, portfolio management, collections, recoveries).
