Role Summary

Senior Data Scientist focused on fraud strategy analytics and operational monitoring across a consumer lending portfolio. You will turn fraud data, scorecard performance, and decisioning outcomes into actionable policy, rule, and reporting recommendations — partnering closely with fraud operations, product, credit/risk, data engineering, and external vendors. Day-to-day responsibilities include monitoring, trend detection, third-party signal assessment, and cross-functional execution.

Key Responsibilities

Translate fraud data and model outputs into clear policy, rule, and threshold recommendations for the decision engine, and partnering with cross-functional teams to prioritize and implement them. Monitor portfolio fraud performance — loss rates, capture rates, false-positive rates, approval impact, vintage trends, and segment-level KPIs — and surface issues with proposed actions. Track scorecard and model performance (PSI, score drift, KS, decay...