The successful candidate will lead the team responsible for the Risk Run Responsibilities across asset classes. He or she will also contribute to the Market and Liquidity Risk framework, and to feasibility studies on new products (including complex derivatives) for the benefit of senior management.
Working within the Quantitative Risk Management Team which is charged with researching, developing, implementing and supporting the analytics used for risk and default management.
These analytics include in particular
• models (calibration, simulation, pricing, sensitivities, Value-at-Risk, liquidity, regulatory capital)
• testing frameworks (back-testing, stress testing, unit and regression testing)
• tools dedicated to clients’ portfolio management (sensitivities, risk reports, margin adequacy, collateral)
The role is divided into two key areas, project work and assistance on daily risk management tasks. The role will be split 50/50 towards the Risk Management tasks.
- Project work and SME input and implementation of Market Data and Risk related change/projects – Significant involvement is required for any development relating to instrument data or validation changes.
- Analysis of the clearing data to look for trends and new business opportunities for LCH.
- BAU margin processing and SME support – Day-to-day validation of any suspect incoming market data. This mostly revolves around Bloomberg/Reuters interrogation/validation. In addition, SME duties are required as a middle agent between technology and the business.
- Margin Management – Responsibility for end to end margin management
- Risk Management Responsibilities – Responsible for the generation of daily, weekly, monthly risk reports, ad-hoc risk management tasks including default management. Limit monitoring, Market and static data management related to Risk Management.
- Validation should be algorithmic and the role of the analyst would be to automate most of the tasks for both existing and new market and static data.
- At least 5 years of work experience Risk Management, heading up a team of Risk Mangers and Market Data experts;
- Thorough knowledge of one or more risk model area's
- Good knowledge of statistics, econometrics, financial mathematics, stochastic calculus or machine learning;
- Able to generate new ideas and to effectively communicate about these ideas;
- Strong analytic skills;
- Highly experienced in modern programming languages (e.g. Matlab, Python) and statistical languages (e.g. SAS, R);
- Affinity with data analytics, (pre)processing, and data handling