Quantitative Risk Analyst

About the role:

• Work with a multi-location team (London & Zurich) on model validation of valuation and risk measurement models covering various asset classes including fixed income, equity, derivatives, insurance-linked derivatives, etc.
• Model review of risk aggregation methodologies such as VaR, Stress and credit risk measurement.
• Model review of financial risk representation in insurance products.
• Model validation tasks require critical analysis of product and modelling technique, model testing (sometimes including independent implementation of the model), alternative model analysis and quantifying model risks.
• Prepare documentation of results and conclusions summarising validation of the model in question according to approved standards. It also includes follow up on identified issues, ensuring resolution or containment.

About the team:

The Financial Model & Valuation Risk Management (FM&VRM) team, is based in London, Zurich and Bangalore, is responsible for ensuring that each material model or tool used to determine valuation or risk characteristics of financial instruments is based on sound mathematical and economic concepts, has been implemented correctly, and produces accurate results. The team also works to develop and maintain the risk methodologies used by FRM to examine risk, and works closely with IT to provide robust, fit for purpose IT platforms to enable FRM's work.

About You:

• Strong academic background, preferably a master's degree or equivalent in a quantitative discipline. A qualification in mathematical finance is preferred. CQF/FRM/CFA is a plus.
• 1+ years of experience in a quantitative role with exposure to financial markets, preferably across asset classes.
• Strong understanding of derivatives pricing theory will be strong advantage.
• Strong written communication skills.
• Possesses proactive attitude and demonstrates curiosity and adaptability to learn new areas and apply general technical knowledge to new specific situations.
• Ability and willingness to examine new systems and methodologies with imperfect documentation.
• Good programming experience to allow independent model replication and automation of model tests to increase productivity. We commonly use R, Python, DAX.