Data Science Lead || Software Product || Mumbai

Prerequisites: ● Experience: 6+ years in Data Science, with at least 3 years specifically in Credit Scoring, Risk Analytics, or Fraud Detection. ● Academic Background: Bachelor’s or Master’s or PhD in Statistics, Mathematics, Computer Science, or Economics. ● Tech Mastery: Expert-level Python, SQL, and hands-on experience with XGBoost, LightGBM, and SHAP for model explainability (or similar algorithms/tools) ● Domain Knowledge: Familiarity with the India Stack, Account Aggregator (AA) frameworks, B2B business & credit cycles and lending product constructs. Core Competencies: ● Algorithmic Architecture: Deep expertise in building PD (Probability of Default) and LGD (Loss Given Default) models using both traditional and alternative data. ● MLOps & Engineering: Knowledge of how to move models from a Jupyter notebook to a production-grade API that handles real-time scoring. ● Regulatory Sensitivity: Ability to build "Glass-Box" models that comply with RBI guidelines on transparency and bias. ● Strategic Leadership: The ability to hire and mentor a team of junior DS/DEs while communicating risk appetite clearly to the Board and Lenders. Success Outcomes Desired: ● At 3 Months: You have audited our current data sources and established a robust ETL pipeline for credit-relevant features. ● At 6 Months: You have deployed our enhanced Credit Scoring Model that outperforms traditional bureau scores by at least 15% in Gini coefficient/KS or comparable statistics. ● At 12 Months: You have built a fully automated Early Warning System (EWS) and a Feature Store that allows our product team to launch new risk-based products in days, not months.