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Derivatives Market Risk Analyst information

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$65K

$108.3K

$145.5K

How much do derivatives market risk analyst jobs pay per year?

As of Sep 9, 2026, the average yearly pay for derivatives market risk analyst in the United States is $108,333.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,000.00 and $131,000.00 per year, depending on experience, location, and employer.

What are popular job titles related to Derivatives Market Risk Analyst jobs?

For Derivatives Market Risk Analyst jobs, the most frequently searched job titles are:

Infographic showing various Derivatives Market Risk Analyst job openings in the United States as of August 2026, with employment types broken down into 85% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $108,333 per year, or $52.1 per hour.

Quantitative Risk Analyst -- Derivatives & Clearing -- Polymarket

Manhattan, NY • On-site

The Bitcoin Street Journal
See more jobs at The Bitcoin Street Journalexternal

$150 - $200/hr

Other

PTO

Posted 5 days ago

Job description

  • Location: NY New York United States
  • Sector: CryptoPerp
  • Source: web3.career
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

Competitive salary & equity

Unlimited PTO

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

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