Senior Fraud Data Scientist

Summary

Join Extend's Fraud & Machine Learning team as a Fraud Analyst and contribute to the company's success by leveraging your data science expertise to detect and prevent fraud. You will analyze large datasets, design and implement fraud detection models, and collaborate with cross-functional teams to develop effective fraud strategies. This role offers the opportunity to work with cutting-edge technology, make a direct impact on the business, and be part of a high-growth, collaborative environment.

Requirements

• Hands-on, proactive, and analytical professionals who are passionate about using data to solve complex, real-world problems
• 3+ years of experience in fraud analytics, ideally within an e-commerce or retail environment
• 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
• Candidates must be located within the continental United States

Responsibilities

• 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

Preferred Qualifications

Prior experience in a startup or high-growth environment is preferred

Benefits

• Competitive salary based on experience, with full medical and dental & vision benefits
• Stock in an early-stage startup growing quickly
• Very generous, flexible paid time off policy
• 401(k) with Financial Guidance from Morgan Stanley