Description:
A leading European bank is looking for an experienced Quantitative Risk Modelling Analyst to join their risk modelling team based in London.
The team’s remit includes all the IMM models in use within the Bank, such as VaR, Stressed VaR, IRC and CRM models in the market risk space, as well as EEPE, Stressed EEPE, Regulatory CVA models in the counterparty risk space. In the context of market risk modelling, the incoming regulation surrounding the “Fundamental Review of the Trading Book” (FRTB) is becoming an increasingly important cornerstone for the team
This is an exciting opportunity to get involved with a variety of interesting projects.
Some of your duties will include:
- Lead methodology projects, gathering and documenting requirements, considering stakeholder interests, regulatory constraints and any potential deficiencies in the current methods exposed by quality assurance processes;
- Investigate, analyse and design risk methods, respecting the aims of accurately capturing risks whilst considering system or other constraints;
- Design, develop and test code changes required to implement the risk methods in the risk systems, whilst assisting the technical teams responsible for optimisation and promotion of the code to the production environment;
- Contribute to the quality assurance processes surrounding risk measurement including back-testing and the VaR Adequacy (P&L Explain) process; cooperate with the risk model validation teams in the review and approval of risk models;
- Support regulatory interactions, participating in industry working groups and Quantitative Impact Studies (QIS);
- In a transactional or advisory capacity, assist risk managers and Front Office in the prompt, accurate and astute risk assessment of deals, where the standard and systematic methods may not be applicable or appropriate.
To be successful in this role, you will have:
- Proven experience in quantitative risk modelling within banking using some of the models mentioned;
- A strong interest and knowledge of risk management best practises, financial markets and economic developments;
- A strong academic background, with at minimum a Masters in mathematics, physics or quantitative finance or equivalent relevant experience;
- A practical knowledge of derivatives, their risk drivers and the models used to price them; sound understanding of stochastic processes and their application to risk factor simulations;
- Exposure to backtesting methodologies, collateral modelling approaches and initial margin models.
- Strong communication skills, both written and verbal;