Quantitative Risk Analyst - Derivatives and Clearing
Polymarket is a decentralized information markets platform that lets users bet on the outcome of real-world events.
Funding history
About Polymarket
Polymarket is an information markets platform where users can trade on the outcomes of various events, leveraging the power of free markets to forecast the future. It provides a mechanism for users to bet on real-world events and earn money based on the outcomes.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will design, implement, and maintain production risk models for market risk, margin, and counterparty exposure. You will build derivatives volatility and correlation models, develop stress tests and auto-liquidation controls, validate AI-assisted work against established frameworks, monitor production performance, and document models to audit-ready standards.
Requirements
- 5–7 years of quantitative risk experience at a clearinghouse, exchange, prime broker, trading firm, or similar.
- Experience designing and implementing enterprise-scale production risk models.
- Experience modeling volatility, correlation, option skews, and option pricing for derivatives, perpetuals, and fully collateralized event contracts.
- Experience with market risk modeling, stress testing, and auto-liquidation mechanics in a clearing context.
- Fluency with AI-assisted development and coding and the ability to validate AI outputs against established risk models.
- Expert-level Python with NumPy, pandas, SciPy, and solid software engineering practices.
- Advanced degree in a quantitative field or equivalent experience.
- Strong foundation in stochastic calculus and linear algebra.
Responsibilities
- Design, implement, and maintain risk models for market risk, margin, and counterparty exposure.
- Build and validate volatility and correlation models for derivatives.
- Develop and run historical, hypothetical, and reverse stress-testing frameworks.
- Design and tune auto-liquidation thresholds, waterfalls, and safeguards.
- Use and rigorously validate AI-assisted models and code before deployment.
- Monitor production model performance, investigate breaks, and iterate quickly.
- Embed risk controls into platform architecture with engineering, trading, and product teams.
- Document model assumptions, limitations, and validation results to audit-ready standards.
Benefits
- Equity