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| Job Location | London |
| Education | Not Mentioned |
| Salary | Competitive salary |
| Industry | Not Mentioned |
| Functional Area | Not Mentioned |
| Job Type | Permanent, full-time |
ABOUT THE PROJECT Context Since the Financial crisis, there has been much debate about the use of internal models to determine regulatory capital requirements: Internal models have become more complex since they were first introduced under Basel II. This has made it increasingly difficult for banks and supervisors to assess whether risks are being mapped correctly and consistently. Many benchmarking studies have highlighted potential inconsistencies as well as high variability in the capital requirements that different banks with similar portfolios have calculated using internal models. Responsibilities The principle requirement of the role will be to contribute to an ambitious project to integrate the counterparty credit risk IMM framework for the prime business by ensuring the bank complies with requirements. This will entail devising / implementing new (or improving existing) risk measurement methods (capital measures, risk factor simulations, etc.), used for regulatory capital calculation and counterparty risk management purposes. The successful candidate will also be responsible for documenting, testing and analyzing impact of modelling assumptions to support downstream review by model validation functions or regulatory bodies. Accordingly, the role does require a solid quantitative background in quantitative counterparty risk. Working in close partnership with quantitative analysts within your team, risk analysts, risk systems and FO, the successful candidate will be expected to: Skills required To be successful in this role, the candidate should meet the following requirements: A strong academic background, with at minima a Masters in mathematics, physics or quantitative finance; Proven experience in a quantitative counterparty risk environment: Counterparty Credit Risk, EEPE, backtesting EEPE & risk factors, EAD, VaR Good knowledge of derivatives, their risk drivers and pricing models; ideally some experience in prime brokerage activity (SFT, Cash / Synthetic prime) Good understanding of risk methodologies and experience with implementation of some modifications would be a plus. Track record of quantitative models implementation, using C# or C++, in a source-controlled environment; Ability to contribute and operate with minimum level of supervision. Ideally: experience with SFT & prime brokerage books