Senior Quantitative Risk Manager: Margin & Pricing

Crypto.com; United States; Hybrid; USD 100,000 - 230,000; Full time

Benefits offered by this job

Competitive salary

401(k) plan with employer match

Health, dental, vision insurance

Work Flexibility Adoption. Hybrid set‑

Internal mobility program

Job summary

Crypto.com is seeking a quantitative Risk Manager to join our global exchange team with a primary focus on margin, pricing, and liquidation models that power our FCM and clearing businesses.

You will own design, calibration, and validation of models, backtest performance, and daily risk monitoring across multi-asset products, while building data pipelines in SQL and Python. Hybrid work available.

Qualifications

• 5+ years of experience in quantitative research, risk management, trading, or related field.
• Master or PhD in a quantitative discipline (math, physics, statistics, engineering, CS, etc.).
• Proficient in Python and SQL/NoSQL data structures and databases.

Responsibilities

• Own margin methodology across the group (SPAN, VaR, portfolio-margining).
• Develop, implement, and validate derivatives pricing models across asset classes.
• Backtest margin coverage and document model performance for regulatory/audit review.
• Build and maintain data pipelines and automated risk reporting in SQL/Python.
• Monitor real-time and historical portfolio risk, including exposure and margin utilization.
• Design automated liquidation logic to balance market risk and impact.

Skills

Python

SQL/NoSQL

Derivatives pricing

Risk management

Margin concepts

Trading/broker-dealer

Cross/Portfolio-Margin

Education

Master or PhD in quantitative field

Tools

SQL databases

Python

NoSQL databases

Job description

Crypto.com is seeking a quantitative Risk Manager to join our global exchange team with a primary focus on margin, pricing, and liquidation models that power our FCM and clearing businesses.

You will own design, calibration, and validation of models, backtest performance, and daily risk monitoring across multi-asset products, while building data pipelines in SQL and Python. Hybrid work available.