# Senior Data Scientist / Analyst, Product

**Company:** [Polymarket](https://hotfix.jobs/companies/polymarket)
**Location:** New York, NY
**Role:** Data Science
**Experience:** 7+ years
**Skills:** SQL, A/B Testing, Experimentation, Product Analytics, Event Tracking, Instrumentation, Causal Inference, Quasi-Experimental Methods, Predictive Modeling, Python, R, Funnel Analysis, Data Modeling, Analytics Engineering
**Posted:** 2026-08-12

> Own product analytics for a consumer prediction-market platform, defining success metrics, designing experiments, and translating behavioral insights into product decisions. The role requires 7+ years of experience, expert SQL, strong experimentation expertise, and excellent product communication.

## Job Description

## Responsibilities
- Partner with product managers, designers, and engineers as the analytical owner for product.
- Define metrics that determine whether a feature worked and communicate plainly when it did not.
- Design, instrument, and analyze A/B tests end-to-end, including sample-size decisions, guardrail metrics, and test stopping criteria.
- Build funnel and behavioral analyses explaining how users find a market, place a first trade, and return.
- Translate user behavior into product direction by identifying drop-off points, friction, and opportunities.
- Own event-tracking specifications and collaborate with engineers to implement accurate instrumentation.
- Work with analytics engineers to promote recurring analyses into modeled datasets.
- Write clear, thorough end-to-end documentation for analyses.

## Requirements
- 7+ years of experience in product analytics, data science, or a similar role supporting a consumer or trading product.
- Expert SQL skills, including querying raw event tables and developing defensible analyses independently.
- Deep experimentation experience, including designing and analyzing production A/B tests and interpreting null results.
- Strong product sense and the ability to form hypotheses about user behavior.
- Hands-on experience defining event tracking and instrumentation.
- Comfort scoping ambiguous questions into rigorous analyses and defending analytical assumptions.
- Strong communication skills, including presenting complex analyses and recommendations to nontechnical audiences.
- Ability to operate effectively in a fast-moving environment with frequently changing business logic.

## Nice-to-haves
- Background in data science, including 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 economics.

## Compensation and Benefits
- Competitive salary and equity.
- Unlimited PTO.
- Full health, vision, and dental coverage.
- 401(k) match.
- Hardware setup including a new MacBook Pro, display, and accessories.

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