My client is a leading global investment bank, operating in numerous locations worldwide, offering multiple financial services.
The quantitative analytics team employs highly specialised quantitative modellers and developers allocated to three broad classes of expertise:
1. Markets teams – located in London, New York, Hong Kong and Singapore – develop and implement modelling solutions supporting the trading operations in the areas of macro, equity, credit and structured products.
2. Risk, finance and treasury (RFT) teams – located in London and New York – design and implement quantitative models for the calculation of regulatory capital, net revenue and balance sheet forecasting, and capital and liquidity planning.
3. central teams support all Markets and RFT groups with project management, coordination among work streams, and the development and maintenance of a common analytic platform.
- Research, development, testing, production implementing and documentation of pricing models fast enough for use in our counterparty credit risk Monte Carlo engine, using modern C++.
- The candidate must follow and support the complete model life cycle and by liaising with our key stakeholders in Risk, the Front Office and IT.
- Deliver prototypes using or extending as appropriate our Python-based modelling platform.
- Develop the models in C++ and assist IT to integrate them into the production system.
- Participate to the design and the development of a robust, scalable, and extendible CCR solution for the bank’s derivatives businesses.
- Support Risk, FO and IT users of our analytics.
- Strong quantitative & analytical skills: The role requires a strong quantitative modeling background based on a PhD or Master’s Degree (or equivalent) in a quantitative discipline such as Math, Science, Economics, Engineering, Quantitative/Math Finance, etc.
- Domain of expertise in any combination of (2 or more products) CCR/XVA, Equity, Commodities, Interest Rates, Inflation, Credit or Foreign Exchange.
- Very strong knowledge of statistics, e.g. regression analysis, reject inference, decision trees, cluster & time-series analysis.
- Track record of producing high quality written communication, and presenting to technical and non-technical audiences.
- Strong programming skills (C++ and / or Python).