Who We Are

About Us

The Options Clearing Corporation (OCC) is the world's largest equity derivatives clearing organization. Founded in 1973, OCC is dedicated to promoting stability and market integrity by delivering clearing and settlement services for options, futures and securities lending transactions. As a Systemically Important Financial Market Utility (SIFMU), OCC operates under the jurisdiction of the U.S. Securities and Exchange Commission (SEC), the U.S. Commodity Futures Trading Commission (CFTC), and the Board of Governors of the Federal Reserve System. OCC has more than 100 clearing members and provides central counterparty (CCP) clearing and settlement services to 19 exchanges and trading platforms. More information about OCC is available at www.theocc.com.

What We Offer

A highly collaborative and supportive environment developed to encourage work-life balance and employee wellness. Some of these components include:

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

Competitive health benefits including medical, dental and vision

Summary

• This role is responsible for one or more functions within Quantitative Risk Management (QRM) who develops and maintains risk models for margin, clearing fund and stress testing with the focus on developing and maintaining risk model software in production, and environments and infrastructure used in model implementation and testing.
• This role will collaborate with other quantitative analysts, business users, data & technology staff, and model validation colleagues to implement new models and enhance existing models.

Primary Duties and Responsibilities:

To perform this job successfully, an individual must be able to perform each primary duty satisfactorily.

• Support the development of quantitative models for pricing, risk management, and stress testing of financial products and derivatives.
• Review model documentation including whitepapers and implementation notes.
• Design, implement, and maintain model prototypes and model testing tools using best industry practices and innovations.
• Review and conduct comprehensive quality assurance testing on the implementation of models and algorithms for both QRM Library and prototypes focusing on requirement verification, coding, and testing quality, which involves the constructions of test cases, automation of model unit testing and creations of reference models if needed.
• Present test plans and test results to, and obtain feedback from peers, model validators, and model developers.
• Participate in code reviews for QRM Library, model prototypes, and Model Development Tool.
• Contribute to the model release testing including margin impact analysis and baseline support and troubleshooting during model library integration with production applications.
• Contribute to the development and testing of Model Development Tool including databases, ETLs, services, orchestration, and CI/CD pipelines.
• Support large-scale model backtesting using historical data, including system configuration, execution and analysis of results.
• Provide integration support to the application consuming QRM libraries.
• Support the launch of new products.
• Provide quantitative analysis and support to risk managers on pricing, margin, and risk calculations.
• Provide production support for numerical libraries and risk management systems as assigned per the QRM’s support schedule.

Supervisory Responsibilities:

None

Qualifications:

The requirements listed are representative of the knowledge, skill, and/or ability required.  Reasonable accommodations may be made to enable individuals with disabilities to perform the primary functions.

• [Required] Strong quantitative skills, ability to demonstrate deep understanding in the following technical areas:
  • Financial mathematics (derivatives pricing models, stochastic calculus, statistics and probability theory, advanced linear algebra)
  • Econometrics, data analysis (e.g., time series analysis, GARCH, fat-tailed distributions, copula, etc.) and machine learning techniques
  • Numerical methods and optimization; Monte Carlo simulation and finite difference techniques
  • Risk management methods (value-at-risk, expected shortfall, stress testing, backtesting, scenario analysis)
• [Required] Good understanding of markets and financial derivatives in equities, interest rates, and