Associate Principal – Model Risk Management – Validation

Associate Principal – Model Risk Management – Validation

Requirements

• 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.)
• Numerical methods and optimization; Monte Carlo simulation and finite difference techniques
• Risk management methods (value-at-risk, expected shortfall, stress testing, backtesting, scenario analysis)
• Financial products knowledge: good understanding of markets and financial derivatives in equities, interest rate, and commodity products
• Basic programming skills. Able to read and write code using a programming language (e.g., Java, C++, Python, R, etc.): Model validation requires ability to write independent code for testing
• Strong problem-solving skills: Be able to accurately identify a problem’s source, severity, and impact to determine root cause and identify potential solutions
• Ability to challenge model methodologies, model assumptions, and review of validation approach.
• Advanced proficiency in writing technical and scientific documentation (e.g., white papers, user guides, etc.).
• Ability to work independently.

Responsibilities

• Review and assess model risk across pricing, margin risk and stress testing of financial products and derivatives.
• Design and implement benchmark models and model-testing tools, including backtesting, using best industry practices and innovations.
• Write and review validation documentation.
• Perform model performance testing, including portfolio back-testing using historical data.
• Review implementation of models and systems focusing on requirement verification.
• Collaborate with other team members in Model Risk Management and Financial Risk Oversight.
• Communicate model risk analysis to CRO teams including Financial Risk Oversight (FRO) and collaborate with other departments at OCC.
• Analyze risk of new products.

Preferred Qualifications

• Experience in database technology and query languages (such as SQL). Non-relational DB and other Big Data, cloud-based computing experience
• Experience in a scripting language such as Python, R or MATLAB
• Experience with numerical libraries and/or scientific computing
• Experience with automated testing frameworks is preferred (e.g., Junit, TestNG, PyTest, etc.)
• Experience with code repository, build and deployment tools (e.g., Git, GitHub)
• Experience in office technology such as PowerPoint, Confluence, Latex, Word, and Excel
• FRM, CFA, etc.
• PhD
• 2+ years of experience in quantitative areas in finance and/or development experience in model implementation and testing