Quantitative Risk Analyst — Derivatives & Clearing

Polymarket•New York, NY

About The Position

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.

Requirements

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

Nice To Haves

C# and/or C++ for performance-critical or production systems
Familiarity with crypto market structure, perpetuals, or prediction markets
Experience with CCP risk frameworks (CPMI-IOSCO PFMI, default management, margin methodology)
Experience building real-time risk systems

Responsibilities

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