You will form part of the Credit Risk Methodology Group, responsible for the development of Counterparty Credit Risk (CCR) exposure models and methodologies for exposure calculations, credit capital calculations and internal risk management. For this role, there is a particular focus is to ensure the requirements from regional regulators and regional entity stakeholders are met across all Trading Book Counterparty Credit Risk activities.
Within this role, you will be responsible for:
- Developing and testing internal CCR exposure models and methodologies across all the asset classes (Equity, Rates, FX, Inflation, Credit, Commodities)
- Enhancing existing simulation models of market factors and pricing models of derivatives
- Prototyping the simulation and pricing models implemented in production for risk analytics and model assessment
- Benchmarking the pricing models in Risk to the models used in trading
- Monitoring and enhancing various Risk frameworks including model backtesting, not Internal Model Method
- Ensuring UK/EU entities complaint with regulatory requirements for Internal Model Method (IMM)
- Responding to regulators with respect to any request regarding the IMM methodology
- Supporting model validation of CCR exposure models globally by delivering quantitative justification and analysis responding to any identified model limitations
- Working in advisory capacity to local and global risk managers and Front Office to ensure risk is appropriately captured in the systems
- Supporting credit risk stress testing methodologies and framework
To be considered for this role it is essential you have demonstrable experience of working within a Counterparty Credit Risk model development function gained within a top tier investment bank, with a key focus on the banks trading book activity. You must have a PHD or MSc in a numerical subject or quantitative discipline such as mathematics, physics, engineering, statistics or computing science. Strong programming skills in Python and C++ are essential and a familiarity with SQL will offer a significant advantage, as would a theoretical understanding and familiarity with derivative pricing models and stochastic calculus.
If you are interested in this role and match the set criteria, please send your CV to Elizabeth.email@example.com