Senior Fraud Data Scientist

3+ years of experience in fraud analytics, ideally within an e-commerce or retail environment Prior experience in a startup or high-growth environment is preferred Bachelor’s degree or higher in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Operations Research, Physics or related field Strong grasp of core data science and analytics concepts, including statistical analysis, modeling, and data wrangling Proficiency in SQL and experience in Python (pandas, NumPy, scikit-learn, etc.) Exceptional communication and stakeholder management skills, with a proven ability to work cross-functionally and influence outcomes High attention to detail, strong intellectual curiosity, and a deep understanding of user behavior and fraud patterns Empathetic, humble, and collaborative team player

Analyze large-scale behavioral, transactional, and interaction data to uncover signals indicative of fraud and abuse Design and implement rules engines, heuristics, and machine learning models to automatically detect and prevent fraudulent activity Apply strong business acumen to rapidly identify actionable insights, analyze fraud patterns, and validate hypotheses Influence business cases and pricing strategies, and contribute to proof-of-concept initiatives with prospective merchants Respond swiftly to emerging fraud threats by developing monitoring frameworks, dashboards, and mitigation solutions in collaboration with cross-functional teams Partner closely with leadership, go-to-market, fraud operations, product, and engineering teams to define and execute effective fraud strategies Champion a culture of continuous learning, experimentation, and collaboration across the fraud and broader data science teams