Lead Associate Principal, Quantitative Risk Management

The OCC • Chicago, IL

1d • Hybrid

About The Position

Duties: Develop models for pricing, margin risking and stress testing of financial products and derivatives. Design, implement and maintain model prototypes, model library and model testing tools using best industry practices and innovations. Implement new models into model library and enhance existing models. Write and review documentations (whitepapers) for the models, model prototypes and model implementation. Perform model performance testing, including portfolio back-testing using historical data. Review implementation of models and algorithms focusing on requirement verification, coding, and testing quality. Conduct comprehensive quality assurance testing on model library including constructions of test cases, automation of model unit testing and creations of reference models if needed. Participate in model code reviews, model release testing (including margin impact analysis and baseline support and troubleshooting during model library integration with production applications) and production support. Implement advanced mathematical and statistical predictive models for risk management using GARCH models, Expected Shortfall models, or Copula-based models. Design and apply model validation and performance monitoring studies using advanced statistical methods such as regression discontinuity designs for causal inference, Kolmogorov-Smirnov tests for data-drift detection, or Kupiec test for Value-at-Risk backtesting. Develop quantitative software using programming languages Python, R or MATLAB, building SQL data extraction pipelines for SQuirrel SQL Client or Microsoft SQL Server, and create quantitative libraries and software repositories with Github. Implement advanced optimization algorithms such as Stochastic Optimization, Markov Chain Monte Carlo or Quadratic Programming. Support the launch of new products. Provide quantitative analysis and support to risk managers on pricing, margin, and risk calculations. Communicate model analysis to professionals across the company and collaborate with cross-functional departments. Up to 40% telecommuting permitted. OCC offers a standard benefits package. This position qualifies for The Options Clearing Corporation’s Employee Referral Program.

Requirements

• Master’s degree in computer science, statistics, mathematics, physics or related and two (2) years of experience as a Quantitative Analytics Specialist, Quantitative Researcher, or related
• Must have work experience with each of the following: 1) implement advanced mathematical and statistical predictive models for risk management using GARCH models, Expected Shortfall models, or Copula-based models; 2) design and apply model validation and performance monitoring studies using advanced statistical methods such as regression discontinuity designs for causal inference, Kolmogorov-Smirnov tests for data-drift detection, or Kupiec test for Value-at-Risk backtesting; 3) develop quantitative software using programming languages Python, R or MATLAB, building SQL data extraction pipelines for SQuirrel SQL Client or Microsoft SQL Server, and create quantitative libraries and software repositories with Github; and 4) implement advanced optimization algorithms such as Stochastic Optimization, Markov Chain Monte Carlo or Quadratic Programming.

Responsibilities

• Develop models for pricing, margin risking and stress testing of financial products and derivatives.
• Design, implement and maintain model prototypes, model library and model testing tools using best industry practices and innovations.
• Implement new models into model library and enhance existing models.
• Write and review documentations (whitepapers) for the models, model prototypes and model implementation.
• Perform model performance testing, including portfolio back-testing using historical data.
• Review implementation of models and algorithms focusing on requirement verification, coding, and testing quality.
• Conduct comprehensive quality assurance testing on model library including constructions of test cases, automation of model unit testing and creations of reference models if needed.
• Participate in model code reviews, model release testing (including margin impact analysis and baseline support and troubleshooting during model library integration with production applications) and production support.
• Implement advanced mathematical and statistical predictive models for risk management using GARCH models, Expected Shortfall models, or Copula-based models.
• Design and apply model validation and performance monitoring studies using advanced statistical methods such as regression discontinuity designs for causal inference, Kolmogorov-Smirnov tests for data-drift detection, or Kupiec test for Value-at-Risk backtesting.
• Develop quantitative software using programming languages Python, R or MATLAB, building SQL data extraction pipelines for SQuirrel SQL Client or Microsoft SQL Server, and create quantitative libraries and software repositories with Github.
• Implement advanced optimization algorithms such as Stochastic Optimization, Markov Chain Monte Carlo or Quadratic Programming.
• Support the launch of new products.
• Provide quantitative analysis and support to risk managers on pricing, margin, and risk calculations.
• Communicate model analysis to professionals across the company and collaborate with cross-functional departments.

Benefits

• A highly collaborative and supportive environment developed to encourage work-life balance and employee wellness.
• A hybrid work environment, up to 2 days per week of remote work
• Tuition Reimbursement to support your continued education
• Student Loan Repayment Assistance
• Technology Stipend allowing you to use the device of your choice to connect to our network while working remotely
• Generous PTO and Parental leave
• 401k Employer Match
• Competitive health benefits including medical, dental and vision

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees