VP Quant Risk Manager

A Leading Financial Organization is seeking to hire a Quantitative Risk Manager into its Quantitative Risk Management team in Chicago. This individual will play a critical role in the development, review, and enhancement of quantitative models supporting margin methodologies, clearing fund calculations, stress testing frameworks, and risk analytics across a complex derivatives clearing environment.

The team is responsible for ensuring the firm's risk models remain robust, responsive to evolving market conditions, and aligned with regulatory expectations. This role offers significant exposure to model development, quantitative research, risk management, and technology initiatives, working closely with senior stakeholders across Financial Risk Management, Model Validation, Compliance, and Engineering. This is an excellent opportunity for a quantitative professional looking to combine hands-on model development with strategic influence over a systemically important financial institution's risk infrastructure

Responsibilities:

• Lead the development, implementation, and enhancement of quantitative models used for margin, clearing fund, pricing, and stress testing activities.
• Research and evaluate model methodologies, perform quantitative analysis, and recommend improvements based on data, market dynamics, and industry best practices.
• Design and maintain model monitoring, backtesting, and performance measurement frameworks to ensure ongoing model effectiveness.
• Partner with Risk Management, Technology, Model Validation, and Compliance teams to support model deployment, governance, and regulatory requirements.
• Prepare technical documentation, present findings to senior stakeholders, and support remediation of validation, audit, or regulatory findings.

Qualifications:

• 5+ years of experience in Quantitative Risk, Model Development, Quantitative Research, Financial Engineering, or a related quantitative function.
• Strong knowledge of derivatives pricing, financial mathematics, statistics, econometrics, risk measurement methodologies, and stress testing frameworks.
• Experience developing or reviewing models related to margin, market risk, clearing risk, derivatives valuation, VaR, expected shortfall, or scenario analysis.
• Advanced programming skills in Python and experience with additional quantitative tools such as C++, Java, R, or MATLAB.
• Demonstrated ability to challenge quantitative methodologies, communicate complex findings, and produce high-quality technical documentation for business and regulatory audiences