Model Risk Governance & Review (MRGR) is a global team of modelling experts within the firm’s Risk Management and Compliance organization. The team is responsible for conducting independent model reviews and governance activities to identify, measure, and mitigate model risk across the firm. Within MRGR, the MRGR Credit Portfolio Group (CPG) Derivatives team manages the model risks associated with XVA and Counterparty Credit Risk (CCR) capital models for JPMorgan’s extensive derivatives portfolios.

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This role offers a unique opportunity to gain exposure to a cross-asset framework that spans multiple lines of business and associated models. It encompasses a broad range of usages including valuation, capital, and credit risk management, and operates in a relatively nascent area marked by ongoing model development and enhancement.

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As a Model Risk Quant Analyst / Associate in Model Risk Governance and Review team, you will conduct comprehensive model review and governance activities across a diverse array of models. These include risk factor simulation engines, correlation and relatedness models, exposure aggregation and end-use models, such as CVA and FVA (Credit and Funding Valuation Adjustments) as well as CCR Regulatory Exposure. Additionally, you will contribute to the expansion of our benchmarking library and the development of related tools, thus bolstering the model validation team’s capacity to independently test models used in the XVA/CCR space.

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Job responsibilities

• Evaluate the conceptual soundness of the models; the adequacy of the testing to support the model assumptions and the correctness of the implementation; the suitability and comprehensiveness of performance metrics and risk measures associated with the use of the model.
• Design and implement experiments to measure on-going model performance and potential impacts of model limitations.
• Evaluate model performance on an ongoing basis and in periodic re-reviews
• Work closely with model developers, trading desk and control functions (Credit Risk and Valuation Control) to understand usage of models within the business context, assess models’ fit-for-purpose for specific portfolios, and syndicate the identified model risks to ensure that they are understood, captured, monitored and managed.
• Contribute to the built-out of the team’s independent benchmarking library.

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Required qualifications, capabilities, and skills

• PhD or MS degree in a quantitative areas (Math Finance, Applied Math, Physics, Engineering or similar)
• Solid grasp of financial math and knowledge of derivative pricing models
• Good command of probability theory, stochastic calculus and numerical methods
• Excellent analytical and problem solving abilities
• Excellent communication skills (written and verbal)
• Inquisitive nature, ability to ask right questions and escalate issues; risk and control mind-set
• Knowledge of programming languages (Python)

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Preferred qualifications, capabilities, and skills

• Experience in model validation or model development
• Familiarity with XVA and Counterparty Credit Risk space more generally

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