Build and evaluate fraud models for onboarding, login, account changes, and money movement. Develop labels, features, sampling strategies, thresholds, and production monitoring to detect account takeover, scams, money mules, and identity fraud. Transition third-party risk models to in-house solutions, measure model performance and drift, collaborate with fraud, risk, operations, and compliance teams, and evaluate AI agent workflows for transaction review and fraud-ring analysis.

Lead payments-focused data science work: build foundational datasets, metrics, and scalable analytics; analyze customer and transaction behavior (including onchain data); conduct strategic analyses to identify product and revenue opportunities; build reporting, dashboards, and automation; and influence product and business strategy through data storytelling to senior stakeholders.