The Model Risk Governance and Review Group (MRGR) oversees model risk at the firm, conducts independent model reviews and provides guidance around a model’s appropriate usage.
As a model risk quant within MRGR Credit Portfolio team, you will carry out validation and governance activities for models used in Counterparty Credit Risk (CCR) space. You will leverage your technical expertise and intellectual rigor to identify, assess and communicate model risks of various component models (risk factor simulation engines and derivatives pricing models) across different asset classes, collateral and exposure aggregation models specific to CCR space, as well as different types of end-usage models such as Credit and Funding Valuation Adjustment (CVA and FVA) for fair valuation, Potential Future Exposure for credit risk management and Regulatory Exposure for capital calculation. Your position will focus on the following activities:
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 (Market/Credit Risk, 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.
Minimum Skills, Experience and Qualifications
We are looking for someone excited to join our organization. If you meet the minimum requirements below, you are encouraged to apply to be considered for this role.
- PhD or MS degree in a quantitative areas (Math Finance, Applied Math, Physics, Engineering, Statistics, Econometrics or similar)
- Solid command of probability theory, stochastic calculus and numerical methods
- Deep understanding of financial math and derivative pricing
- 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)
Additional Skills, Experience and Qualifications
The following additional items will be considered but are not required for this role
- Experience in model validation or model development
- Knowledge of other programming languages, such as C++