Quantitative Risk Management Director

Overview

A leading Clearing Corporation with offices in Chicago and Dallas is seeking a Director level candidate to join their Quantitative Risk Management (QRM) group. The firm is expanding its leadership team to support the development and enhancement of advanced models used for margin, clearing fund, pricing, and stress-testing across derivatives and financial products.

This individual will serve as a senior technical leader driving model innovation, leading prototype development, integrating analytics into production risk systems, and managing a high-performing team of financial engineers and model developers. The role offers significant visibility across the organization, partnering closely with Financial Risk Management, Model Validation, IT, and Compliance, while also engaging with regulators on high-impact model initiatives.

• Direct and oversee development of pricing, margin, and stress-testing models for derivatives and financial products.
• Lead research on model methodologies, assess industry best practices, and drive prototype development for new model features.
• Design tools, procedures, and performance-monitoring frameworks to evaluate model effectiveness.
• Lead implementation of model analytics within the QRM Library and support integration into firmwide risk systems.
• Lead remediation of model validation or regulatory findings and prepare materials for regulatory inquiries.

• Master s degree in a quantitative field required (Math, Financial Engineering, Computer Science, Physics, etc.);
  PhD preferred.
• 10+ years of quantitative model development/research experience in financial markets.
• Deep expertise in derivatives pricing, stochastic calculus, probability, statistics, and advanced linear algebra.
• Strong background in econometrics, time-series analysis, GARCH, copulas, and machine learning techniques.
• Proficiency with risk management methods:
  VaR, Expected Shortfall, stress testing, and backtesting.
• Ability to challenge modeling assumptions, identify limitations, and articulate complex concepts clearly.
• Strong documentation skills, including technical papers, methodology documents, and user guides.