Marketplace Risk Operations Analyst (Night Shift)

Why you’ll love this role

You're more than a case reviewer—you’re an investigator. You enjoy tackling complex fraud cases where the answer isn’t obvious, connecting signals across accounts, transactions, and behaviors to uncover larger patterns.

You work confidently with AI-powered tools, using your judgment to validate or challenge recommendations and help improve detection systems through structured feedback.

You're naturally curious about how fraud evolves and stays ahead of emerging threats, contributing insights that strengthen risk controls and enforcement strategies.

What you’ll do

• Investigate complex and escalated fraud cases across accounts, transactions, listings, buyers, and sellers that require human judgment.
• Identify coordinated fraud, abuse patterns, and emerging threats by connecting signals across accounts, devices, geographies, and transaction history.
• Surface actionable fraud trends, insights, and recommendations to Risk Operations and Enforcement teams.
• Review AI-generated case recommendations, make informed decisions on edge cases, and provide feedback to improve models and rules.
• Execute enforcement actions accurately and within SLA requirements.
• Document investigations with clear, evidence-based findings for escalations, policy reviews, and potential law enforcement requests.
• Identify detection gaps and improve fraud monitoring effectiveness.
• Contribute insights during calibration sessions and fraud pattern reviews.

About You

• 3+ years of experience in Fraud Operations, Trust & Safety, Risk Operations, or a similar investigative role.
• Hands-on experience with fraud detection tools such as SEON, Sardine, Sift, or similar platforms; SQL or BI tool knowledge is a plus.
• Strong analytical skills with the ability to identify patterns across accounts, geographies, and transaction behavior.
• Excellent written communication and investigation documentation skills.
• Comfortable working in human-in-the-loop AI environments, critically evaluating model recommendations rather than relying on them blindly.