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Polymarket is a rapidly growing prediction market platform enabling users to trade on real-world outcomes across politics, economics, sports, culture, and current affairs. The company has facilitated $115B in trading volume and is positioning itself as a trusted source for market-based probability forecasting.
You will own end-to-end growth analytics for one of Polymarket's vertical teams (sports, crypto, politics, or finance). This is a high-ownership role where you set the analytical agenda, not respond to requests. You'll be embedded within your vertical team, accountable for understanding user acquisition, conversion to active traders, and retention patterns.
Key responsibilities include: managing full-funnel GTM analytics from paid acquisition through first trade to repeat engagement; partnering with marketing on spend efficiency metrics (CAC, ROAS, payback period, channel mix); sizing and prioritizing growth opportunities within your vertical; designing and interpreting experiments across creative, lifecycle, and onboarding; building cohort, funnel, and retention analyses; serving as the analytical voice in vertical planning; collaborating with analytics engineers to operationalize recurring analyses; and documenting work clearly for team accessibility.
You'll need 7+ years in growth, marketing, or product analytics with a track record of owning a business area end-to-end. Expert SQL proficiency is essential—you should move from raw event tables to defensible answers independently. Deep fluency in full-funnel GTM metrics (CAC, ROAS, payback, conversion rate, retention, LTV) and judgment about when each is misleading is required. You should have experience embedded with marketing and product teams as a true partner, comfort with ambiguity and scoping vague questions into rigorous analyses, and strong communication skills for translating complex analyses to non-technical audiences. The role demands comfort in fast-moving environments where business logic changes frequently.
Plus factors include data science background (experimentation design, causal inference, predictive modeling in Python/R), genuine interest or expertise in one of the verticals, and experience in fintech, crypto, prediction markets, or data-intensive financial products.
