Analyst - Market Risk - VaR

The major responsibilities of this role is related 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 value 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.