Senior Data Scientist

About the role

Polymarket is seeking a Senior Data Scientist / Analyst, Growth to serve as the dedicated analytical owner for one of its vertical teams, including sports, crypto, politics, or finance. In this position, you will own the full-funnel GTM analytics for your assigned vertical, determining how users discover the platform, what converts them into active traders, and what drives long-term retention. You will set the analytical agenda for your vertical by deciding what metrics matter, directing marketing spend toward the highest-impact opportunities, and challenging the current plan when the data indicates a better path forward. This role operates in a fast-moving environment where new markets launch constantly and the growth playbook must adapt in real time, requiring comfort with rapid change and frequent re-prioritization. You will be the primary analytical voice for your vertical, translating complex findings into clear recommendations that non-technical stakeholders can act on without friction. The position demands ownership of business outcomes rather than participation in a request queue, meaning you define the questions, build the analyses, and are accountable for the impact of your insights. You will work closely with cross-functional partners, especially marketing and analytics engineering, to ensure that growth experiments, creative tests, and onboarding flows are measured rigorously and improved iteratively based on evidence.

Key facts

What you'll do

Own full-funnel analytics for your vertical, from paid acquisition through first trade to repeat engagement, and be the person who can explain what is driving each step of the journey.

Partner with marketing on spend efficiency by analyzing CAC, ROAS, payback period, and channel mix, then make data-driven recommendations on where incremental dollars should be allocated for maximum impact.

Size and prioritize growth opportunities within your vertical by evaluating which leagues, events, or market types deserve investment and estimating the likely return and risk profile of each option.

Design and read experiments across creative variations, lifecycle messaging, and onboarding flows, and maintain a clear line of sight on what worked, what did not, and why.

Build cohort, funnel, and retention analyses that reveal how users in your vertical behave differently from the broader platform and surface insights that apply specifically to your market.

Serve as the analytical voice in your vertical's planning process by setting targets, defining success metrics, and holding the team accountable to agreed-upon goals and results.

Collaborate with analytics engineers to transform recurring analyses into durable, maintainable models and pipelines instead of one-off queries that do not scale.

Write end-to-end documentation that is clear and thorough enough that any teammate can understand your methods, replicate your work, and continue your analyses without friction.

Evaluate the quality and reliability of data sources, identify gaps or inconsistencies, and ensure that key business decisions are based on robust and well-understood inputs.

Champion a culture of experimentation and learning by sharing results, surfacing patterns across tests, and proposing follow-up analyses that compound insights over time.

Requirements

Bring 7 or more years of experience in growth, marketing, or product analytics, with a demonstrable track record of owning a business area end-to-end and driving measurable outcomes.

Possess expert-level SQL skills, enabling you to move directly from raw event tables to defensible answers without relying on intermediate support or hand-holding.

Demonstrate deep fluency in full-funnel GTM metrics, including CAC, ROAS, payback period, conversion rate, retention, and LTV, and exercise sound judgment in knowing when each metric can be misleading or requires additional context.

Have prior experience embedded within marketing and product teams as a strategic partner in the work, rather than functioning as a downstream request queue that merely executes analyses after decisions are made.

Be comfortable operating in situations with ambiguity, where questions are initially vague and you must scope a rigorous analysis, defend your assumptions, and iterate as new information emerges.

Communicate effectively with both technical and non-technical audiences, taking complex analyses and landing clear, actionable recommendations for stakeholders who may not be familiar with data jargon.

Remain productive and focused in a fast-moving environment where business logic changes frequently, markets update in real time, and you must keep pace without sacrificing analytical rigor.

Possess a data science background that includes experimentation design, causal inference, or predictive modeling, with hands-on experience in Python or R, even if it is used only to validate analyses or prototype approaches.

Show a genuine interest or demonstrated expertise in one or more of the platform's core verticals, such as sports, crypto, or politics, and understand the dynamics that drive engagement in those domains.

Have experience in fintech, crypto, prediction markets, or other data-intensive financial products, where regulatory, security, and accuracy considerations are central to decision-making.

Nice to have

Only candidates who meet all of the listed requirements and have a strong track record in the specified domains will be considered for this role.

Practical notes

This role is based in New York and requires in-person presence.

The engagement is full-time.

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