Principal Associate, Data Scientist - Bank Customer Protection Debit & Claims
Core
Build real-time machine learning models to detect and prevent debit card fraud and claims issues, protecting customers from fraudulent activities.
Role type
Principal Associate, Data Scientist (Fraud Detection)
Builds
Real-time decision systems for debit authorization fraud detection
Domain
Financial Services / Fraud Prevention
Deliverable
production ML models
Required skills
Gradient boosting (XGBoost, LightGBM, H2O), Python, SQL, Spark, model backtesting, validation, performance measurement, cross-functional project coordination
Preferred skills
Production-quality Python (pytest, mypy, linting), MLOps (Kubeflow Pipelines on Kubernetes), handling highly imbalanced datasets, graph and sequence learning
Technologies
Python, Conda, AWS, H2O, Spark, SQL, Kubeflow Pipelines, Kubernetes, XGBoost, LightGBM
Responsibilities
Partner with cross-functional teams to deliver products keeping customers safe from fraud; build ML models through design, training, evaluation, validation, and implementation; leverage big data stacks to reveal insights in numeric and textual data; translate technical complexity into tangible business goals
Seniority
Principal, hands-on IC with strategic impact
