Data Scientist, Fraud Risk

Job Summary

Focused on enhancing fraud detection, the full-time remote Data Scientist, Fraud Risk will manage onboarding fraud decisioning, build predictive models, and collaborate with cross-functional teams to combat identity theft and application abuse.

Key responsibilities

• Own and improve onboarding fraud decisioning across the application journey, including identity verification and fraud models
• Build, validate, deploy, and monitor models to detect various forms of fraud using diverse data signals
• Design and analyze A/B tests and other experimental strategies to balance fraud losses against approval rates and verification friction

Required qualifications

• 5 to 8+ years of experience in data science, risk analytics, or a related quantitative field, preferably in a high-growth startup or fintech environment
• Strong proficiency in Python and SQL for model building and data transformation
• Experience with predictive modeling for fraud, identity, KYC, or related adversarial classification problems
• Deep understanding of statistical inference, experiment design, and model validation techniques
• Ability to evaluate decision systems using metrics such as fraud capture and operational workload