Market Risk Quant TRIM / C# - C++
Lunalogic UK is looking for an experienced Marlet Risk Quant analyst to work in the context of the Targeted Review of Internal Models (TRIM) within our client's Market Risk Team.
The team requires a quantitative analyst with excellent programming skills
to help deliver new analytics and requirements related to the market risk model monitoring process. The successful candidate will develop analytics required for off-production analyses and play a key role in integrating analytics in a production environment, in close collaboration with our colleagues in the RISK Systems team.
Working in close partnership with Risk Management quantitative analysts and developers, and RISK Systems personnel, the successful candidate will be expected to:
This is mainly a developer role.
- Develop a sound understanding of the proposed methodologies and quantitative requirements.
- Develop, maintain and improve algorithmic code required to implement changes to existing environments (production and off-production).
- Relay the quantitative requirements and constraints to the developers, business analysts and architects of co-operating teams, so as to ensure that the target architecture is designed to operate flexibly and efficiently, as well as undertake developments & maintenance activities.
- Act as Risk Management representative in the project roll-out: advise on methodology requirements, perform user acceptance testing, etc.
Accordingly, the role does require a solid quantitative background within a market risk environment
. Continuous interaction with other teams in RISK and FO will also call for strong communication skills
- A strong academic background with Masters in mathematics, physics or quantitative finance;
- Excellent programming skills in C++, C# and Java. C# and Python knowledge is highly desirable.
- Proven experience in a quantitative finance market risk modelling environment
- Design and implementation in a source-controlled environment; knowledge of continuous integration / continuous delivery approaches with particular focus on automated testing