Senior Data Scientist, ML— Fraud Detection & Effectiveness

Senior Data Scientist, ML— Fraud Detection & Effectiveness

The Opportunity We are seeking an experienced Senior Machine Learning Data Scientist to build fraud and abuse detection models and measure how effectively they work. This role combines hands-on modeling with deep experimentation, evaluation, and analytics to improve detection and quantify business impact. You will work across the fraud lifecycle — from modeling and ground-truth definition to performance measurement, monitoring, and executive-ready insights! What you'll Do

• Build and tune ML models for fraud and abuse detection using statistical and classical ML techniques.
• Develop robust evaluation frameworks, datasets, and metrics to measure model and mitigation effectiveness.
• Analyze false positives/negatives, model drift, and emerging fraud patterns to continuously improve detection.
• Define ground truth, labeling approaches, and fraud taxonomies that support reliable model development and evaluation.
• Design experiments and evaluate tradeoffs across precision, recall, customer impact, and fraud loss.
• Build dashboards and metrics that translate detection performance into measurable business impact.
• Pressure-test models and data for leakage, bias, data-quality issues, and other sources of misleading results.
• Partner across engineering, product, policy, and risk teams to turn insights into detection improvements and business decisions.

What you'll need to succeed

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