Data Scientist (Fraud)

Responsibilities

• Prototype, evaluate, and help produce machine learning models for fraud detection; own their ongoing monitoring and retraining cycles.
• Design and run experiments to measure the impact of fraud interventions, balancing customer experience against loss reduction.
• Size fraud typologies across our product lines to inform prioritization and investment decisions.
• Build and maintain anomaly detection systems to surface novel fraud vectors before they scale.
• Work closely with fraud operations, engineers, product managers, and data analysts to translate model outputs into real-world mitigations.
• Experience & Background
• A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar).
• 3+ years of experience in data science, decision science, or risk analytics within fraud, payments, or financial crime.
• Hands-on experience building and deploying machine learning models in a production environment.
• Fraud, risk, or financial services experience is a strong plus.

Languages