Principal, Quantitative Risk Management

What You'll Do:

This role is responsible for leading project development, implementation, testing and maintenance of models used for margin, clearing funds and stress testing. The range of responsibilities varies depending on his/her focus within QRM, that includes research and development of significant model features, leading prototype development and testing, designing tools for model performance monitoring, managing or providing technical leadership for model prototypes, implementing and supporting integration of model code library into OCC risk systems. This role will work closely with risk managers in Financial Risk Management and partners in other areas, including Information Technology, Model Validation, and Compliance.

Primary Duties and Responsibilities:

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

• Lead, support and review development and implementation of models for pricing, margin risk and stress testing of financial products and derivatives

• Provide analysis of new products and support their implementation at OCC

• Research and present model alternatives based on academic literature, industry best practices, data analysis and model prototyping

• Produce high quality whitepapers and technical documentation following QRM’s procedures and templates

• Develop standards, procedures and tools for model performance monitoring and communicate results to peers and leadership

• Lead and direct implementation of the model development tools in QRM supporting model analysis and backtesting

• Lead and direct implementation of the model analytics in the QRM Library

• Partner with IT and other departments delivering QRM analytics to production

• Provide production support, 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

• Provide intellectual leadership promoting innovation and learning

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: seasoned level in understanding of markets and financial derivatives in equities, interest rate, and commodity products

• [Required] Seasoned level in programing skills

• [Required] Advanced proficiency in using a programming language (e.g., Java, C++, Python, R, MATLAB, etc.) in a collaborative software development setting. Model development and prototyping require advanced development skills in Python and data mining

• [Required] Strong problem-solving skills and be able to accurately identify a problem's source, severity, and impact to determine possible solutions and needed resources

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

• [Required] Seasoned level in technical and scientific documentation (e.g., whitepapers, user guides, etc.)

Technical Skills:

• [Required] Expert in database technology, query languages (such as SQL), and efficient storage and serialization protocols

• [Required] For model development and prototyping role: expert in a scripting language such as Python, R or MATLAB

• [Required] Experience with numerical libraries and/or scientific computing including numerical optimizers (e.g. NAG, MATLAB)

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

• [Required] Experience with CI/CD and DevOps tools (e.g., Git, GitHub and various profiling and telemetry tools) is required for model implementation and application development

• [Required] Experience with high performance computing, distributed computation engines and cloud computing