Quantitative Risk Modeling Manager

Overview

A leading financial market infrastructure organization is seeking a Senior Manager, Quantitative Risk Modeling to drive the design, development, and implementation of advanced models used for margin, clearing fund, and stress‑testing analytics.

In this role, you will lead a team of quantitative developers and financial engineers, guide research innovation, own key model frameworks, and partner with Technology, Risk Management, Model Validation, and Compliance to deliver mission‑critical analytics.

• Lead the design and implementation of pricing, margin, and stress‑testing models for derivatives and financial products.
• Oversee analysis and onboarding of new financial products into risk frameworks.
• Research, evaluate, and present model alternatives using academic literature, industry benchmarks, and prototype testing.
• Produce clear, high‑quality technical documentation, whitepapers, and model specifications.
• Develop standards and tools for model performance monitoring and communicate findings to leadership.
• Direct implementation of quantitative analytics into production systems in partnership with engineering teams.
• Provide production support and troubleshoot model‑related, system‑related, or data‑related issues.
• Lead remediation efforts for model validation findings or regulatory feedback.
• Present material for regulatory reviews and senior risk committees.
• Manage, mentor, and develop a team of quantitative modelers and financial engineers.

• Master’s degree in Computer Science, Mathematics, Physics, Finance, Financial Engineering, or another quantitative field.
• 10+ years of quantitative research or financial model development experience.
• 5+ years managing technical or quantitative teams.
• Advanced knowledge of derivatives pricing, stochastic calculus, statistics, econometrics, and risk modeling.
• Expertise in numerical methods, Monte Carlo simulation, optimization, and scientific computing.
• Deep understanding of financial markets and derivatives across equities, interest rates, and commodities.
• Advanced programming skills in Python (required) plus experience with Java, C++, R, or MATLAB.
• Expert SQL/database skills; familiarity with efficient data storage and serialization techniques.
• Experience with testing frameworks (e.g., PyTest, JUnit), CI/CD pipelines, Git/Git Hub, and distributed/cloud computing.
• Strong documentation skills and the ability to challenge assumptions, methodologies, and model designs.

• Experience with high‑performance computing and advanced numerical optimization libraries.