Senior Data Scientist / Analyst, Product

Polymarket is looking for a Senior Data Scientist / Analyst to be the analytical partner to our product team and the person who can say whether what we shipped actually worked. You'll own product insights end-to-end, from defining its success metrics, to designing the experiments that test them, to telling the team what the results mean. This is a role for someone with real product instincts, not just query skills. You'll spend as much time forming hypotheses about why users behave the way they do as you will validating them, and you'll be expected to push back when a feature's numbers don't support the story being told about it. You'll do it all in a fast-moving environment where we ship constantly and the answer is usually needed before the next release.

Responsibilities

Partner with product managers, designers, and engineers as the analytical owner for product; Define the metrics that determine whether a feature worked, and be the person willing to say plainly when it did not; Design, instrument, and read A/B tests end-to-end, including the calls on sample size, guardrail metrics, and when to stop a test; Build the funnel and behavioral analyses that explain how users find a market, place a first trade, and come back for the next one; Turn user behavior into product direction. Surface where people drop off, what the friction actually is, and what is worth building next; Own the event tracking spec for your area, working with engineers so instrumentation lands correctly the first time rather than being reconstructed later; Work with analytics engineers to promote your recurring analyses into modeled datasets rather than one-off queries; Write end-to-end documentation that’s clear and thorough enough that anyone on the team can pick up your analysis without friction

Requirements

7+ years in product analytics, data science, or a similar role supporting a consumer or trading product; Expert SQL. You can go from raw event tables to a defensible answer without help; Deep experimentation experience. You have designed and read A/B tests in production, and you can explain a null result without spinning it; Strong product sense. You can look at a funnel and form a hypothesis about the user behind it, not just describe the number; Hands-on experience defining event tracking and instrumentation, and the patience to get it right; Comfort with ambiguity. You can scope a vague question into a real analysis and defend the assumptions you made along the way; Strong communication. You can take a complex analysis to a non-technical audience and land the recommendation; Comfortable operating in a fast-moving environment where business logic changes frequently and you need to keep pace

Nice to have

Data science background - causal inference, quasi-experimental methods, or predictive modeling in Python or R; Experience with trading, marketplace, or other two-sided products where user behavior drives the economics

Benefits

Competitive salary & equity; Unlimited PTO; Full Health, Vision, & Dental coverage; 401k match; Hardware setup: new MacBook Pro, big display, & accessories