Quant Risk Analyst - Derivatives & Clearing
At a glance
Mid-level Risk & Financial Compliance role at Polymarket. New York · full-time · $400,000–$450,000 base.
financeroles summary, based on the employer's posting.
What you'll do
- Build and maintain production models for market risk, margin and counterparty exposure in a clearing operation
- Model derivatives volatility and correlation, then calibrate, backtest and validate those models
- Run historical, hypothetical and reverse stress tests, and tune liquidation triggers, waterfalls and safeguards
- Use AI tools to speed development, then test their outputs against established risk methods before deployment
- Track production model results, investigate breaks, document validation and work with engineering, trading and product teams
What you bring
- Five to seven years in quantitative risk at a clearinghouse, exchange, prime broker, trading firm or similar setting
- You have built enterprise-scale risk models for production, including derivatives volatility, correlation and option pricing
- Hands-on clearing experience with market risk, stress testing and automated liquidation mechanics
- Expert Python skills, a quantitative graduate degree or equivalent experience, and a strong base in stochastic calculus and linear algebra
Who this fits
This mid-level, hands-on role suits someone who builds and validates quantitative risk models in production and can challenge AI-generated work against established methods. You’ll work in person from the New York City office alongside trading, engineering and risk teams.
From the employer
About Polymarket
Polymarket is the world's largest prediction market platform, where people trade on the outcomes of real-world events. As our markets, volumes, and derivative product suite grow, so does the sophistication of the risk infrastructure behind them. Our clearing and risk systems must operate with the rigor of a traditional clearinghouse while moving at the speed of a crypto-native trading platform.
The Role
We're hiring a mid-level 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 (VaR/ES, SPAN-style margining, GARCH-family volatility models, standard correlation frameworks) 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, option pricing and implementing 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 (numerical stack: 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 Have
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.
Pay Transparency
Base salary range: $400,000 to $450,000, plus equity and benefits.
This is a good-faith range for the level we're hiring at. Experience varies widely within a title here, so if your expectations fall outside it, reach out anyway. We're always happy to talk it through.
Location & Work Setup
This role is based in our New York City office, in person. You'll be working directly alongside the trading, engineering, and risk teams.
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