Quantitative Risk Analyst — Derivatives & Clearing

Polymarket
New York, NY
On-site

Who this role is best for

Best suited to candidates with enterprise risk modeling experience working in derivatives and clearing environments.

Best fit for

  • Candidates with 5–7 years of clearinghouse or exchange risk modeling experience
    — “5–7 years of quantitative risk experience at a clearinghouse, exchange, prime broker, trading firm, or similar
  • Individuals with deep expertise in volatility, correlation, and option pricing for trad-fi derivatives
    — “Deep experience modeling volatility, correlation, option skews, and option pricing at scale for trad-fi derivatives
  • Candidates who can integrate AI tools into risk modeling while maintaining rigorous validation
    — “Use AI tools extensively to accelerate model development, coding, and research — and rigorously validate AI outputs against established risk models before deployment

Things to consider

  • Requires fluency in Python with strong software engineering practices for production systems
    — “Expert-level Python (NumPy, pandas, SciPy; solid software engineering practices)
  • Highly technical role with a focus on model validation and real-time risk systems
    — “Monitor model performance in production, investigate breaks, and iterate quickly

How to stand out

  • Highlight experience with stress testing and auto-liquidation systems in clearing contexts
    — “Develop and run stress-testing frameworks: historical scenarios, hypothetical shocks, and reverse stress tests
  • Demonstrate a track record of building and maintaining enterprise-scale risk models
    — “Proven expertise designing and implementing risk models at enterprise scale — production systems, not just research prototypes
  • Showcase ability to validate AI-generated models against traditional risk frameworks
    — “pressure-testing AI-generated models and code against well-established risk frameworks before anything ships
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • design and implement enterprise-scale risk models
  • build and validate volatility and correlation models
  • develop stress-testing frameworks
  • design and tune auto-liquidation logic
  • monitor model performance in production
Typical background
5-7 years of quantitative risk experienceadvanced degree in a quantitative field

Skills & requirements

Required

Quantitative Risk ExperienceRisk ModelsMarket Risk ModelingStress TestingAuto-liquidation MechanicsPython (numpy, Pandas, Scipy)Ai-assisted Development And Coding

Preferred

C#C++Crypto Market StructureCCP Risk Frameworks

Stack & domain

PythonNumPyPandasScipyAI ToolsC#C++LeadershipCommunicationProblem SolvingDecision MakingFinanceRisk ManagementDerivativesClearing Operation

About the role

Original posting from Polymarket via Ashby

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

Source: Polymarket careers (Ashby)

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