Senior Data Scientist (Credit Risk)

Develop and deploy predictive models across the credit lifecycle (acquisition, risk, and collections) with a focus on improving approval quality and loss performance.

Translate model outputs and analysis into actionable credit strategy, including approval cutoffs, segmentation, and decision rules.

Analyze portfolio performance (FPD, delinquency, loss) to identify key drivers of deterioration and recommend targeted actions.

Evaluate tradeoffs between approval rate, loss, and profitability, and recommend strategies to optimize portfolio performance.

Distinguish fraud risk vs credit risk, improving early default performance and reducing losses.

Design and execute experiments (A/B tests, champion/challenger frameworks) to evaluate strategies and drive continuous improvement.

Work with Product and Engineering to implement decisioning logic into production systems and ensure accurate execution.

Monitor model and strategy performance over time, identifying drift, instability, or unintended impacts on portfolio outcomes.

Collaborate cross-functionally with other departments to ensure decisions align with business goals and risk appetite.