# Quantitative Researcher at Polymarket

- Company: Polymarket
- What the company does: Polymarket is the world’s largest prediction market, allowing you to stay informed and profit from your knowledge by trading on future events across various topics. Backed by General Catalyst and Founders Fund.
- Company website: https://polymarket.com/
- Type: Startups
- Level: Mid level
- Location: New York
- Work setup: On-site
- Pay: $250K to $350K base salary per year (USD)
- Posted: 2026-09-15
- Apply by: 2026-10-30
- Apply: https://jobs.ashbyhq.com/polymarket/a8f161f3-2126-4888-aa6e-74e23ae49686
- Page: https://www.1752.vc/careers/jobs/polymarket-quantitative-researcher/

## About the role

Polymarket is launching perpetual futures, and this role is the mathematical foundation the exchange runs on. You'll be the first dedicated quant on the perps product, working directly with the engineering team to build the pricing and risk infrastructure from the ground up. Your mandate covers the core mechanics of the exchange: how mark prices are constructed, how funding rates are designed and calibrated, and how margin parameters are set when new assets get listed.

## What they're looking for

- Quant experience at a perpetuals exchange or HFT firm, with direct, hands-on ownership of mark price construction, funding rate design, or margin modeling in production
- Deep understanding of perp exchange mechanics — you can design and defend a complete funding rate formula, index aggregation methodology, and margin tier model from first principles, including how each breaks under adversarial or illiquid conditions
- Strong market microstructure intuition: you understand how prices form across venues, how liquidity and staleness distort aggregated signals, and what happens to a multi-source index when sources disagree or go dark
- The ability to implement your own research — you write rigorous specs and then build them in code, you do not hand off to engineers and walk away
- Strong programming skills in Python, comfortable writing production-quality code, not just research notebooks
- Rigorous thinking about edge cases: your models account for violent market moves, data outages, and source conflicts before they happen, not after

Tags: Engineering