Senior Data Scientist, ML— Fraud Detection & Effectiveness
Core
Build and tune ML models for fraud and abuse detection, define ground truth, and measure model effectiveness to quantify business impact.
Role type
Senior Machine Learning Data Scientist (Fraud Detection)
Builds
Production ML models for fraud detection and evaluation frameworks
Domain
Financial risk / Adversarial domains
Deliverable
production ML models
Required skills
Statistical and classical ML, Python, SQL, Model evaluation, Experimentation, Data visualization, Model monitoring, Handling imperfect labels
Preferred skills
Anomaly detection, Clustering, Behavioral modeling, Weak supervision, LLMs for evaluation, Multi-layered risk controls
Technologies
Python, SQL
Responsibilities
Build and tune ML models for fraud detection, Develop evaluation frameworks and metrics, Analyze false positives/negatives and model drift, Define ground truth and fraud taxonomies, Design experiments to evaluate tradeoffs, Build dashboards for business impact
Seniority
Senior, hands-on IC
