Lead Associate Principal, Quantitative Risk Management

What You'll Do:

The Lead Associate Principal This role is responsible for one or more functions within Quantitative Risk Management (QRM) to develop and maintain risk models for margin, clearing fund and stress testing: model analytics and performance monitoring; model prototyping and testing; and model implementation. 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.

• 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 (such as whitepapers and techinical documentations) 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

• Provide production support, participate in troubleshooting and analysis of model, system and data issues

• 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 OCC and collaborate with cross-functional departments

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] Financial mathematics (derivatives pricing models, stochastic calculus, statistics and probability theory, advanced linear algebra)

• [Required] Econometrics, data analysis (e.g., time series analysis, GARCH, fat-tailed distributions, copula, etc.) and machine learning techniques

• [Required] Numerical methods and optimization; Monte Carlo simulation and finite difference techniques

• [Required] Risk management methods (value-at-risk, expected shortfall, stress testing, backtesting, scenario analysis)

• [Required] Financial products knowledge: good understanding of markets and financial derivatives in equities, interest rate, and commodity products

• [Required] Basic programing skills: able to read and/or write code using a programming language (e.g., Java, C++, Python, R, MATLAB, etc.) in a collaborative software development setting

• [Required] Problem-solving skills: Be able to identify a problem's possible source, conduct study and provide reasoning in estimating severity and impact

• [Required] Ability to challenge model methodologies, model assumptions, and validation approach

• [Required] Experience in technical and scientific documentation (e.g., white papers, user guides, etc.)

• [Required] Business-oriented and responsible

• [Required] Good team player

Technical Skills:

• [Required] Experience in database technology and query languages (such as SQL). Non-relational DB and other Big Data, cloud-based computing experience

• [Preferred] Experience in Java is required for model implementation (Java 8 or later)

• [Required] Experience in a scripting language such as Python, R or MATLAB

• [Preferred] Experience with numerical libraries and/or scientific computing

• [Preferred] Experience with automated testing frameworks is preferred (e.g., Junit, TestNG, PyTest, etc.)

• [Preferred] Experience with code repository, build and deployment tools (e.g., Git, GitHub, Jenkins)

• [Required] Experience with software design: effective application of design patterns, expertise in object-oriented design is required for model implementation

• [Preferred] Experience wi