Analyze large-scale behavioral, transactional, and interaction data to uncover signals indicative of fraud and abuse
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
Requirements
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
Candidates must be located within the continental United States.
Benefits
Competitive salary based on experience, with full medical and dental & vision benefits.
Stock in an early-stage startup growing quickly.
Generous, flexible paid time off policy.
401(k) with Financial Guidance from Morgan Stanley.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.