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Polymarket is the world's largest prediction market platform, enabling individuals to trade on real-world outcomes across politics, economics, sports, culture, and current affairs. The platform operates as a peer-to-peer marketplace with no centralized house, aggregating diverse opinions into transparent, market-based probabilities. With $21B traded in 2025 and rapid growth, Polymarket aims to become a ubiquitous beacon of truth in global media.
The Markets team owns what gets listed on Polymarket, how markets are structured, and whether they function effectively. This Data Scientist role is the dedicated analytical layer informing nearly every team decision. Currently, much of this work is manual, ad hoc, or absent entirely. The successful candidate will build infrastructure for understanding market health, model liquidity dynamics, and help the team make smarter decisions on listings, liquidity provider rewards, and market viability.
Key responsibilities include: modeling liquidity dynamics to identify drivers of healthy order flow and inform reward structures; building and maintaining recurring reports on market health metrics; auditing new market listings using historical and comparable data to recommend approval, adjustments, or rejection; analyzing underperforming markets to diagnose root causes; partnering weekly with the Markets team to scope, prioritize, and deliver decision-ready outputs; developing frameworks for evaluating market success; and identifying gaps in data collection or instrumentation.
This is a high-ownership role requiring someone who thinks seriously about market mechanics. You will not receive a backlog of tickets; instead, you'll identify important questions, answer them, and deliver actionable insights. The ideal candidate has strong Python and SQL proficiency, deep working knowledge of market structure (order books, spreads, liquidity provision, market design tradeoffs), and a track record of owning analyses end-to-end from ambiguous questions to stakeholder-ready outputs. Experience at prediction markets, trading firms, or funds with market structure exposure is highly valued. Familiarity with automated market makers, CLOB mechanics, decentralized exchange design, or liquidity incentive programs is a plus.
