Senior Data Scientist

About the role

Polymarket is seeking a Senior Data Scientist to serve as the primary analytical partner for the product team, owning the complete lifecycle of product insights from initial hypothesis through to clear communication of results. The hire will define what success looks like for new features, rigorously design and oversee A/B tests, and interpret results to inform product decisions. This role requires deep product instincts and the ability to translate complex data into actionable narratives for both technical and non-technical stakeholders. You will be the person who can definitively say whether a feature worked and why, pushing back on assumptions when the data contradicts the story. The position operates at the speed of a fast-moving product environment where answers are needed before the next release. You will build behavioral funnels that reveal how users discover markets, take their first trades, and return for subsequent engagement. This role involves significant ownership of event tracking specifications to ensure data quality from the start rather than through retrospective fixes. You will work closely with analytics engineers to evolve ad hoc queries into reusable, modeled datasets that serve the entire organization.

Key facts

What you'll do

Partner with product managers, designers, and engineers as the analytical owner for product initiatives across the platform.

Define the key metrics that determine whether a feature is successful, establishing the guardrails and success criteria before launch.

Design, instrument, and read A/B tests end-to-end, including determining appropriate sample sizes, selecting guardrail metrics, and deciding when to stop or iterate.

Build and analyze funnels and behavioral models that explain how users find a market, place a first trade, and come back for the next one.

Turn user behavior data into concrete product direction by identifying friction points and prioritizing the next set of features to build.

Own the event tracking spec for your area, collaborating with engineers to ensure instrumentation is implemented correctly the first time.

Work with analytics engineers to convert recurring analyses into modeled datasets and persistent insights rather than one-off queries.

Write comprehensive end-to-end documentation that is clear and thorough enough for any team member to understand and reuse your analysis.

Surface where users drop off in the conversion funnel and quantify the actual friction to prioritize high-impact improvements.

Champion data literacy across the organization by explaining complex analytical findings to non-technical audiences and landing clear recommendations.

Requirements

Bring 7 or more years of experience in product analytics, data science, or a similar role supporting a consumer or trading product.

Possess expert SQL capabilities, able to move from raw event tables to a defensible answer without assistance or extensive debugging.

Have deep experience designing and reading A/B tests in production, including the ability to explain a null result without making excuses.

Demonstrate strong product sense, capable of looking at a funnel or dataset and forming a hypothesis about the user behavior behind the numbers.

Have hands-on experience defining event tracking and instrumentation, with the patience to get the specifications right before implementation.

Be comfortable operating in environments with high ambiguity, able to scope a vague question into a concrete analysis and defend the assumptions made.

Communicate effectively, taking complex analytical results and presenting them to a non-technical audience in a way that drives decision-making.

Thrive in a fast-paced environment where business logic changes frequently and you can keep pace while maintaining analytical rigor.

Possess a data science background, including knowledge of causal inference, quasi-experimental methods, or predictive modeling in Python or R.

Have prior experience with trading, marketplace, or other two-sided platforms where user behavior directly impacts economic outcomes.

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.

Practical notes

Full-time position based in New York.

Candidates must be authorized to work in the United States without sponsorship for this role.

The application review process will close once the role is filled.