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New York, New York, United States
Onsite
Polymarket is the world's fastest growing prediction market. We enable individuals to express views on real-world events by trading on outcomes across politics, economics, sports, culture, and current affairs. Built as a peer-to-peer marketplace with no centralized "house," Polymarket aggregates diverse opinions into transparent, market-based probabilities that reflect collective expectations about the future.
We're growing fast, both in terms of volume ($115B traded to date) and adoption as an alternative news source. Our ambition is to become a ubiquitous beacon of truth in global media and we need your help adding fuel to the fire.
Polymarket is looking for a Senior Data Scientist / Analyst, Risk to find the patterns that indicate abuse on our platform: fake and duplicate signups, farmed bonuses, collusive or manipulative trading, etc, and to turn what you find into controls that hold. You'll work closely with product and compliance, sitting between the data and the decisions about who gets to trade and under what conditions.
This is a role for someone who enjoys adversarial problems. The behavior you're looking for is actively trying not to be found, and the signal is usually in how accounts act together rather than in any single field. You'll be expected to build the detection, quantify the exposure, and make a clear recommendation about what to do about it. And you'll do it in a fast-moving environment where every new product opens new abuse vectors.
Investigate and quantify abuse across the funnel, including multi-accounting and fake signups, bonus and promotion farming, wash trading, collusion, and market manipulation
Build detection logic that separates genuine users from coordinated behavior, combining on-chain, device, and behavioral signals rather than relying on any one of them
Turn one-off investigations into monitoring, including recurring reporting and alerting that surfaces new patterns without someone having to go looking
Size the financial exposure of each abuse vector so the team can prioritize by what it actually costs rather than by how alarming it looks
Partner with product on controls at the points of friction: onboarding, verification, bonus eligibility, and measure whether they worked without driving away legitimate users
Support compliance with the analysis behind investigations, escalations, and regulatory reporting
Work with analytics engineers to promote your detection logic into the modeled layer so it runs reliably instead of living in a notebook
Own documentation end-to-end — including the thresholds and rationale behind your detection logic, written clearly enough that compliance or any engineer can follow it without you in the room
7+ years in risk, fraud analytics, trust and safety, or a similar investigative analytical role
Expert SQL. You can pursue a hypothesis across large behavioral datasets without supervision
Pattern recognition instinct. You can look at a cluster of accounts and articulate what they share and why it is unlikely to be coincidence
Experience building detection rules or models, and honesty about the tradeoff between false positives and missed abuse
Sound judgment about user impact. You understand that every control has a cost to legitimate users, and you can weigh the two
Comfort working alongside compliance, and the discretion to handle sensitive findings appropriately
Comfortable operating in a fast-moving environment where business logic changes frequently and you need to keep pace
(Plus) Experience with on-chain analysis, wallet clustering, or blockchain forensics
(Plus) Experience with trade surveillance, market manipulation detection, or AML
(Plus) Statistical or machine learning background — anomaly detection, graph analysis, or clustering in Python or R
(Plus) Experience in fintech, crypto, prediction markets, or other data-intensive financial products
Competitive salary & equity
Unlimited PTO
Full Health, Vision, & Dental coverage
401k match
Hardware setup: new MacBook Pro, big display, & accessories