Expert Data Modeler, Fraud Risk Detection
Core
Build fraud detection models and features to identify high-risk activity while minimizing friction for legitimate customers.
Role type
Senior IC data scientist (fraud risk)
Builds
Production-ready fraud detection models and features for financial institutions
Domain
Financial services / Fraud risk
Deliverable
production ML models
Required skills
Python, PySpark, supervised learning, model evaluation, feature engineering, statistical inference, experimentation, model calibration, handling class imbalance, model drift mitigation
Preferred skills
Experience with distributed or cloud data systems, experience moving models into production
Technologies
Python, PySpark, pandas, NumPy, scikit-learn, XGBoost, TensorFlow
Responsibilities
Investigate large datasets to identify fraud patterns and behavioral signals; Translate ambiguous fraud problems into clear hypotheses and model requirements; Develop and validate predictive features using identity, transactional, and behavioral data; Write clean, efficient, well-tested code for batch, retro, or real-time decisioning environments; Monitor feature quality, model performance, and fraud-pattern drift; Design and present analyses for model behavior and tradeoffs
Seniority
Senior, hands-on IC
