# Senior Data Scientist / Analyst, Growth

**Company:** [Polymarket](https://hotfix.jobs/companies/polymarket)
**Location:** New York, NY
**Role:** Data Analytics
**Experience:** 7+ years
**Skills:** SQL, Python, R, Cac, Roas, Payback Period, Conversion Rate, Retention Analysis, Ltv, Experimentation, Causal Inference, Predictive Modeling, Cohort Analysis, Funnel Analysis, Marketing Analytics
**Posted:** 2026-08-12

> Owns full-funnel growth analytics for a vertical, guiding acquisition spend, experimentation, retention, and investment priorities. The role requires 7+ years of growth, marketing, or product analytics experience, expert SQL, strong GTM metric fluency, and effective cross-functional communication.

## Job Description

## Responsibilities
- Own full-funnel analytics for a vertical, from paid acquisition through first trade and repeat engagement.
- Partner with marketing on CAC, ROAS, payback period, spend efficiency, and channel mix.
- Size and prioritize growth opportunities across leagues, events, and market types.
- Design and analyze experiments across creative, lifecycle, and onboarding initiatives.
- Build cohort, funnel, and retention analyses to compare vertical user behavior with the broader platform.
- Provide analytical input for planning, target-setting, and accountability.
- Work with analytics engineers to turn recurring analyses into durable models.
- Write clear, thorough end-to-end documentation for analyses.

## Requirements
- **7+ years** in growth, marketing, or product analytics, with experience owning a business area end to end.
- Expert SQL skills, including working from raw event tables to defensible conclusions.
- Strong knowledge of CAC, ROAS, payback period, conversion rate, retention, and LTV.
- Experience embedded with marketing and product teams as a strategic partner.
- Ability to scope ambiguous questions into rigorous analyses and defend assumptions.
- Strong communication skills with both technical and non-technical audiences.
- Comfort working in a fast-moving environment with frequently changing business logic.

## Nice-to-haves
- Data science experience with experimentation design, causal inference, or predictive modeling in Python or R.
- Interest or expertise in sports, crypto, or politics.
- Experience in fintech, crypto, prediction markets, or other data-intensive financial products.

## 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, large display, and accessories.

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