Director, Quantitative Risk Management

125 S. Franklin Street, Suite 1200, Chicago, IL 60606

Director, Quantitative Risk Management

Direct the development, implementation, testing and maintenance of models used for margin, clearing fund and stress testing. Develop methodology and Python prototype implementation for implied volatility simulation model enhancements to generate coherent implied volatility surfaces across maturities and strikes. Execute quantitative risk model enhancement initiatives addressing validation and regulatory findings, including interest rate risk add-ons and short-dated options modeling enhancements. Conduct quantitative risk model performance monitoring and margin backtesting exceedance attribution analysis using Python and SQL, including investigation of symbol- and strategy-level drivers, and identification of model limitations and potential enhancement opportunities.

Support new product launching initiatives by participating in discussions with exchanges and internal stakeholders, assessing whether existing quantitative risk models can support new products, coordinating model enhancement discussions, and partnering with technology teams on testing and implementation activities. Work closely with risk managers in Financial Risk Management and partners in other areas, including Information Technology, Model Validation, and Compliance. Manage a team of financial engineers and model developers, and direct, lead, and review the development and implementation of models for pricing, margin risk, and stress testing of financial products and derivatives.

Oversee the analysis of new products and drive their implementation, and research and present model alternatives based on academic literature, industry best practices, data analysis, and model prototyping. Produce whitepapers and technical documentation following QRM’s procedures and templates, and develop standards, procedures, and tools for model performance monitoring while communicating results to peers and leadership. Lead and direct the implementation of model development tools in QRM supporting model analysis and back testing, as well as the implementation of model analytics in the QRM Library.

Partner with IT and other departments to deliver QRM analytics to production, provide production support, and participate in troubleshooting and analysis of model, system, and data issues. Lead remediation of Model Validation or regulatory findings, prepare and present materials supporting management and regulatory inquiries, and provide intellectual leadership promoting innovation and learning. Up to 40% telecommuting permitted. OCC offers a standard benefits package.

* This position qualifies for The Options Clearing Corporation’s Employee Referral Program.*

Master’s degree in finance, financial engineering, financial mathematics, or related and six (6) years of experience as a quantitative risk management analyst, quantitative risk management principal, or related

Must have work experience with each of the following:
1) Developing methodology and Python prototype implementation for implied volatility simulation model enhancements to generate coherent implied volatility surfaces across maturities and strikes;
2) Executing quantitative risk model enhancement initiatives addressing validation and regulatory findings, including interest rate risk add-ons and short-dated options modeling enhancements; and
3) Conducting quantitative risk model performance monitoring and margin backtesting exceedance attribution analysis using Python and SQL, including investigation of symbol- and strategy-level drivers, and identification of model limitations and potential enhancement opportunities.…