Senior Data Scientist, Risk & Fraud Analytics
Overview
You will lead detection engineering for abuse and manipulation at Polymarket, the fastest-growing prediction market with $115B in trading volume. You will own the full risk analytics loop: investigating suspicious account behavior, building detection logic, and sizing financial exposure. You will partner directly with product and compliance teams to implement controls that protect the platform without alienating legitimate users. This role is for someone who thrives on adversarial problems where the signal hides in account clusters and behavioral patterns.
What You'll Do8
- 1Investigate and quantify abuse vectors such as multi-accounting, fake signups, bonus farming, wash trading, and market manipulation.
- 2Build detection logic that separates genuine users from coordinated behavior using SQL, Python, and on-chain signals.
- 3Turn one-off investigations into recurring monitoring and alerting systems that surface new abuse patterns automatically.
- 4Size the financial exposure of each abuse vector and recommend prioritization based on actual costs.
- 5Partner with product to implement controls at onboarding, verification, and bonus eligibility, and measure their impact on legitimate users.
- 6Support compliance with analysis for investigations, escalations, and regulatory reporting.
- 7Collaborate with analytics engineers to formalize detection logic into the modeled data layer.
- 8Document detection thresholds and rationale clearly for engineering and compliance teams.
Requirements10
- 17+ years in risk, fraud analytics, trust and safety, or similar investigative analytical roles.
- 2Expert SQL skills to pursue hypotheses across large behavioral datasets without supervision.
- 3Strong pattern recognition to identify coordinated account behavior and articulate commonalities.
- 4Experience building detection rules or models, with an understanding of false positive and false negative tradeoffs.
- 5Sound judgment on user impact, balancing abuse prevention with legitimate user experience.
- 6Comfort working alongside compliance and handling sensitive findings with discretion.
- 7Ability to adapt to a fast-moving environment with frequently changing business logic.
- 8Plus: On-chain analysis, wallet clustering, or blockchain forensics.
- 9Plus: Trade surveillance, market manipulation detection, or AML experience.
- 10Plus: Statistical or machine learning background, including anomaly detection, graph analysis, or clustering in Python or R.
Salary Insight
Salary not disclosed in listing
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