AddressWe offer:
The major responsibilities of this role relate to the development and specification of quantitative methodologies, which are used to measure market risk.
Each analyst is aligned with a business cluster (e.g. Equities, Rates etc.), and has the following responsibilities for their cluster:
- Understand the products traded and trading strategies used.
- Identify all sources of market risk.
- Develop and specify the VaR model.
- Understand and monitor the VaR model's performance.
- Ensure that any risk not captured by the VaR model is measured within the Risks-not-in-VaR framework.
- Ensure that any significant tail-risk is highlighted to the Scenarios team.
- Support the development and specification of the Economic Risk Capital (ERC) model.
- Collaborate closely with the Model Validation group to ensure that the risk sensitivities used for risk calculations are appropriate.
- Collaborate closely with the data team to ensure that the historical data used in VaR or ERC calculations are appropriate.
- Collaborate closely with the Strategic Change Management (SCM) team, to ensure that any changes to methodology are appropriately project-managed for implementation.
- Ensure that all risk models are adequately documented for both internal and external (e.g. regulatory) purposes
You offer:
- The candidate should have a first degree in mathematics, theoretical physics, econometrics, statistics or engineering, followed by a Ph.D / Masters in Science in one of those areas or in finance.
- The role would suit a candidate with experience in quantitative risk measurement within an investment bank or, more broadly, with experience in a quantitative role within finance.
- It is essential that the candidate has a very good understanding of financial mathematics, and in particular an understanding of derivative instruments and the risks they generate.
- He or she also needs to understand the effects, and relative importance, of underlying risk factors upon the v alue of the instruments.
- A very strong mathematical background is essential. In addition a background in statistics, time series analysis and probability theory would be of particular interest.
- Problem solving skills, as well as computational and communication skills, are essential.
- The candidate should be able to explain complicated concepts clearly to all members of staff, and present their proposals in a clear and precise manner to senior management and regulatory bodies.
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