Fraud Data Scientist

You will analyze fraud models and rules across payment rails and merchant segments. You will identify emerging fraud patterns, explore and validate new signals, manage label-quality feedback loops, design experiments, evaluate vendors, tune risk strategies, and produce clear performance reporting for stakeholders.

Responsibilities

• Analyze fraud model and rule performance by merchant segment
• Identify emerging fraud patterns and quantify their impact
• Explore transaction, device, behavioral, identity, and network signals
• Prototype and validate model features
• Manage ground-truth labels and feedback loops
• Design and analyze backtests, shadow tests, and champion-challenger experiments
• Evaluate third-party fraud vendors
• Recommend rules, thresholds, authentication, and decision strategies
• Create explainable reporting on model decisions and performance

Requirements

• 4+ years of data science or analyst experience in fraud, risk, or abuse
• Strong SQL and Python skills
• Knowledge of fraud-model statistics and machine-learning concepts
• Understanding of card-not-present fraud, account takeover, card testing, friendly fraud, and chargebacks
• Experience evaluating messy, imbalanced, delayed-label data
• Experience designing and analyzing experiments
• Ability to explain model behavior and tradeoffs to stakeholders
• Experience with graph or network analysis is a plus
• Experience with AI-native tooling or willingness to use it

Benefits

• Equity