Senior Data Scientist

As a Lead Data Scientist in credit risk modeling, you’ll drive the development of our clients next-generation consumer credit scoring and portfolio valuation models. You will design, build, and maintain real-time Probability of Default (PD) models using both statistical and machine learning techniques, ensuring they integrate seamlessly into underwriting and economic return optimization frameworks.

You’ll create robust calibration methodologies, uphold regulatory and fairness standards, and experiment with innovative approaches including leveraging LLMs for explain ability and feature engineering. Partnering closely with cross-functional teams, you’ll translate modeling insights into actionable credit strategies, guide junior team members, and contribute to our clients long-term modeling roadmap.

Who you are

• 5+ years of experience in credit risk modeling across consumer lending, credit cards, or BNPL.
• Deep expertise in PD model development, validation, and calibration.
• Advanced proficiency in Python and SQL; comfort with XGBoost, scikit-learn, pandas, and MLflow.
• Experience with explainability tools like SHAP, LIME, and PDP.
• Strong communication skills, with the ability to influence technical and non-technical stakeholders.
• Familiarity with real-time modeling and trends in ML and credit analytics.

Great to have

• Experience using LLMs to derive features from unstructured data (e.g., customer communications, application text).
• Knowledge of integrating third‑party credit bureau data into production environments.
• Understanding of champion–challenger modeling and A/B testing frameworks.
• Exposure to loan-level economic modeling, including cost‑of‑capital and loss metrics.