Quantitative Risk Analyst — Derivatives & Clearing

Job Description

About Polymarket
Polymarket is the world's largest prediction market platform. We enable individuals to express views on real-world events by trading on outcomes across politics, economics, sports, culture, and current affairs. Built as a peer-to-peer marketplace with no centralized "house," Polymarket aggregates diverse opinions into transparent, market-based probabilities that reflect collective expectations about the future.
We're growing fast - both in terms of volume ($21B traded in 2025) and adoption as an alternative news source. Our ambition is to become a ubiquitous beacon of truth in global media and we need your help adding fuel to the fire.

About the Role
Polymarket is hiring a Quantitative Risk Analyst to design and implement enterprise-scale risk models at the heart of our clearing operation. You'll own models for market risk, volatility and correlation of derivatives, stress testing, and automated liquidation - the systems that keep the platform solvent and users protected in fast-moving markets.
This is a hands-on role: you'll be building models in production code, not just specifying them. We expect you to work fluently with AI tools for development and research - and to be the skeptic in the room, pressure-testing AI-generated models and code against well-established risk frameworks before anything ships.

What You'll Do

- Design, implement, and maintain enterprise-scale risk models covering market risk, margin, and counterparty exposure for a clearing organization

- Build volatility and correlation models for derivatives, including calibration, backtesting, and ongoing model validation

- Develop and run stress-testing frameworks: historical scenarios, hypothetical shocks, and reverse stress tests

- Design and tune auto-liquidation logic - trigger thresholds, liquidation waterfalls, and safeguards against cascading liquidations

- Use AI tools extensively to accelerate model development, coding, and research - and rigorously validate AI outputs against established risk models before deployment

- Monitor model performance in production, investigate breaks, and iterate quickly

- Partner with engineering, trading, and product teams to embed risk controls into platform architecture

- Document model assumptions, limitations, and validation results to an audit-ready standard

What We're Looking For

- 5-7 years of quantitative risk experience at a clearinghouse, exchange, prime broker, trading firm, or similar

- Proven expertise designing and implementing risk models at enterprise scale - production systems, not just research prototypes

- Deep experience modeling volatility, correlation, option skews, and option pricing at scale for trad-fi derivatives, perpetuals, and fully collateralized event contracts

- Hands-on experience with market risk modeling, stress testing, and auto-liquidation mechanics in a clearing context

- Strong fluency with AI-assisted development and coding, paired with the judgment to pressure-test AI outputs against well-established risk models and catch what looks plausible but is wrong

- Expert-level Python (NumPy, pandas, SciPy; solid software engineering practices)

- Advanced degree in a quantitative field (math, statistics, physics, financial engineering, CS) or equivalent experience

- Strong mathematical foundation in stochastic calculus and linear algebra

- (Plus) C# and/or C++ for performance-critical or production systems

- (Plus) Familiarity with crypto market structure, perpetuals, or prediction markets

- (Plus) Experience with CCP risk frameworks (CPMI-IOSCO PFMI, default management, margin methodology)

- (Plus) Experience building real-time risk systems

Benefits

- Competitive salary & equity

- Unlimited PTO

- Full Health, Vision, & Dental coverage

- 401k match

- Hardware setup: new MacBook Pro, big display, & accessories