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Polymarket is the world's largest prediction market platform, enabling users to trade on outcomes across politics, economics, sports, culture, and current affairs. The platform aggregated $21B in trading volume in 2025 and is positioned as an alternative news source reflecting collective expectations about future events.
The Trust and Safety team is responsible for maintaining the integrity of the US exchange by identifying fraud, flagging AML-adjacent activity, and preventing bad actors from eroding market quality. As Senior Data Analyst, you will own the analytical layer of this operation, sitting on the Data team while working directly with Trust and Safety leadership.
Key responsibilities include: writing SQL queries to investigate suspicious trading activity from initial flag through resolution; fielding ad hoc data requests from the Trust and Safety team and delivering clear, well-documented answers independently; building and maintaining monitoring dashboards that track fraud and AML signals on an ongoing basis; identifying patterns in bad actor behavior across accounts, trading history, and on-chain data, then translating those patterns into concrete detection logic improvements; documenting investigation findings in formats that non-technical stakeholders can act on; and working with the T&S team to prioritize high-risk signals and reduce noise in existing alerting systems.
You will work on live, real-money markets where analytical work has immediate consequences. The goal is to enable the Trust and Safety team to focus on decisions rather than data pulls.
Required qualifications: 3–5 years of data analysis experience with a track record of delivering under ambiguity; strong SQL skills with ability to write clean, efficient queries against unfamiliar schemas and debug independently; direct experience in fraud detection, AML investigation, or trust and safety analytics at an exchange, fintech, or similar environment; proven ability to scope and complete open-ended investigations independently; experience building dashboards that operations or compliance teams rely on as a primary source of truth; clear communication skills to explain findings and implications to non-technical audiences.
Desirable qualifications include familiarity with crypto or prediction market data structures, on-chain activity, or exchange-level trading data; experience writing or contributing to detection logic or rules engines in fraud or AML contexts; and background working directly with compliance, legal, or operations teams in regulated environments.
