Senior Data Scientist

What you'll do

• Build and evaluate fraud models for onboarding, login, account changes, and money movement.
• Transition fraud detection from third-party vendor scores to in-house models.
• Define label taxonomies and data requirements to ensure all events become training data.
• Design holdout and exploration sampling to measure false negatives and incorrect blocks.
• Track fraud rates, dispute rates, and precision across customer segments to set loss budgets.
• Backtest, monitor drift, and retrain models on the company's fraud platform.
• Build and evaluate AI agent workflows for transaction review and fraud-ring analysis.

What we're looking for

• 5+ years in data science or applied ML on fraud, risk, or financial crime.
• Advanced Python and SQL skills.
• Experience with XGBoost, LightGBM, or similar machine learning frameworks.
• Experience building models with sparse, delayed, or biased labels, including cold start and reject inference.
• Strong statistics skills in anomaly detection, graph or network methods, experimentation, and threshold optimization.
• Experience taking models to production and monitoring them.
• Clear communication with technical and non-technical partners.
• Fintech, payments, crypto, or card fraud experience, including chargebacks and disputes (preferred).