Polymarket Quant Risk Analyst

About the Company: We are an early-stage startup building the financial infrastructure for prediction markets. We believe prediction markets will become the largest derivatives product class globally, and we are building the lending layer that enables institutions and advanced traders to maximize capital efficiency against these positions.

Note: To maintain confidentiality during this early stage, specific company details will be shared during the interview process.

The Role: As our first dedicated Quant hire, you will design the mathematical core that determines protocol safety, liquidation logic, and capital efficiency. This is not a role for building autonomous AI trading agents; this is about building the risk infrastructure that powers the next generation of on-chain liquidity.

You will own the risk framework from day one, solving unique challenges associated with illiquid, binary assets where closed-form solutions do not apply.

What You'll Do

Design the Liquidation Engine: Define LLTV, partial-liquidation logic, penalties, keeper/auction flows, and circuit breakers tailored for prediction market collateral. Build RFQ & Pricing Models: Create a quoting system where users submit collateral portfolios → models simulate future price paths → protocol returns risk-adjusted loan quotes. Oracle & Microstructure: Design robust mark prices, slippage & spread haircuts, and time-to-resolution adjustments for illiquid assets. Risk & Margin Modeling: Model cross-margin netting rules, correlation haircuts, and exposure caps per event/category. Simulation & Backtesting: Run simulations on historical order book data; calculate extreme-VaR/ES and tune parameters for insolvency vs. utilization.

Who You Are

MUST HAVE Experience: 3–5 years of experience (This is the sweet spot for high-impact ownership; 10+ years may be misaligned with the current comp structure). MUST HAVE Background: Pure quantitative trading firm experience. Exceptional candidates with deep TradFi/Crypto risk engineering backgrounds will be considered. Education: MSc or PhD in a quantitative subject (Math, Physics, CS, Stats) is highly preferred. Domain Knowledge: Experience pricing binary options, insurance, perps/margin, or DeFi lending risk. Deep understanding of market microstructure (distinguishing market maker behavior vs. passive liquidity during volatility spikes). Tech Stack: Strong Python for simulation/backtesting; comfort with TypeScript is a plus.

Why Join?

Founding Impact: Define the risk framework for an institutional primitive in a high-growth category. Equity Upside: We offer a founding-team level equity share proportion for the right fit. Technical Ownership: Your models will directly determine protocol safety and scalability. No legacy code.

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