- Permanent, Full time
- Anson McCade
- London, England, United Kingdom
- Full time
Quant Analyst - Credit Quant Team - Fixed Income ETF - Assoc/VP
My client is looking for a Quantitative Analyst to join the Credit Quant Team, within the Markets Quantitative Analysis (MQA) department, to support the Fixed Income ETF Business in London.
The Credit Quantitative Analysis team is a global team of quants located on three trading floors worldwide: in London, New York and Hong Kong. The team's mandate is to provide quantitative support for the trading and structuring teams in Credit Markets. The main focus of the group includes: pricing methodologies, hedging strategies, risk management and analytics development. The quantitative analysts work closely with trading, structuring, IT, risk management, finance and other control functions to have a better understanding of risk and P&L and add value to the business.
The ETF business is a new growing initiative within Markets. This role provides an opportunity to learn about how ETFs work and different aspects of Fixed Income markets. It also offers the opportunity to work in a closely integrated team comprised of traders, quants and technologists, with exposure to all aspects of the operation. The candidate must be practically minded - he or she must understand how models generate value for the trading operation, what level of sophistication is needed to achieve their goals while remaining simple and practical to implement, and how model performance can be evaluated both in testing and production environments. The position requires both attention to details and the ability to see the big picture of the trading operation.
- Research and implement optimization algorithms and market making models for the Fixed Income ETF business
- Implementation of ETF pricing and risk models in the C++ Front-Office Analytics library
- Building tools for P&L, hedging analysis, stress-testing in Python/ Kdb/Excel/VBA
- Research and implement optimal execution algorithms for the Creation/Redemption of ETFs
- Automation of flow analysis and improvements to hedging efficiency and hedge execution algorithms
- Work on general efficiency improvements and optimization, including: performance, memory management, GPUs
- Working on day-to-day support of the business
- Experience in Numerical Analysis, Statistical Methods, Probability and Stochastic Calculus, Optimization and Machine Learning techniques.
- Knowledge of ETFs, Fixed income Products and Market Microstructure. Familiarity with systematic trading models (optimal execution algorithms, statistical arbitrage, algorithmic market making)
- Fluency in mathematical finance and statistical analysis. Ability to work with large datasets.
- Strong programming skills using Python, R, C++/C# or Java. Proficiency in database applications, such as Kdb, and visualization tools.
- Attention to details. Ability to work in a team and to work well under pressure in a Front-Office environment
- Strong verbal and written communication skills
- PhD or MSc in Mathematics, Physics, Engineering, Finance or Economics