Lead and grow a data science team building predictive models for credit risk and payments. Drive integration with product and engineering, run quarterly planning, mentor scientists, adopt AI-assisted and agentic workflows, and collaborate on model infrastructure and deployment.

Build, test, deploy, and monitor ML models for credit risk, fraud detection, and transaction timing. Create training datasets, run experiments and A/B tests, analyze customer trends, and collaborate with Engineering, Product, and Business teams to deliver end-to-end data science solutions.

Lead development, deployment, and monitoring of underwriting, risk, fraud, and payments ML models. Own full modeling lifecycle, feature engineering, validation, A/B testing, cross-functional collaboration, and mentor junior data scientists.