Eames Consulting is currently partnered with an Investment Manager in London, searching for a Quantitative Risk Analyst to join their Quantitative Risk team, part of Group Risk.
This is a permanent role sitting within the Quantitative Risk team with a focus on investment and risk modelling. As a Quantitative Analyst, you will be exposed to models used across all asset classes, as well as originating and being involved in the development of quantitative approaches across the different risk functions. The breadth of model types means that you will have practical knowledge not only of financial mathematics (risk-neutral pricing theory, stochastic calculus) but also statistical and econometric methods.
Responsibilities include (but not limited to):
- The independent review of internally-created models such as asset allocation algorithms, quantitative strategy tools, risk and capital management tools, pricing models and the review of vendor-supplied investment systems
- Developing, advising on and assisting with quantitative risk modelling and methodologies e.g. operational risk loss models, capital requirement calculation methodologies, risk metric specifications, stress testing approaches, etc.
- Producing written model review/validation reports and participating in building and strengthening the overall model governance framework for the firm
- The production of software tools to assist in the risk management process
- The review and challenge of new products or portfolio constructions where these involve complex products and / or complex combinations
- Proactively contributing to initiatives and projects that will benefit from quantitative approaches
Skills and Competencies
Variety of strong quantitative knowledge – with practical experience preferably gained on the buy side
- Good technical knowledge of market, investment and operational risk; technical knowledge of credit risk is desirable
- Strong interpersonal skills: tact, patience, courtesy; must be able to challenge teams whilst building and maintaining positive relationships
- Team player able to build strong relationships with the wider Risk team and work collaboratively with stakeholders
- Understanding of model validation principles and techniques, again preferably gained on the buy-side
- Robustness under challenge: must be willing to recommend necessary changes and defend these under pressure
- Ability to work under own initiative is essential; must be proactive in identifying points of weakness and suggesting solutions
- Strong knowledge of Excel and proficient in VBA; familiarity with / the ability to code in Matlab is highly desirable. Experience of coding in Python, R and SQL will be looked on favourably
