- CDI, Plein-temps
- Anson McCade
- Londres, Angleterre, Royaume-Uni
Rates Strats – E-Trading Engineering – Assoc/VP level - London based
The role offered is to maximize the consistency of the performance across a range of algorithmic trading tools. This includes the opportunity to work closely with Quant Analysts and other Quant Developers mapping out performance targets, understanding the intention of each algorithm’s behavior and delivering entirely automated tests to verify that these are being met. It requires a strong technical skillset and a desire to see the end of manual test plans.
E-Trading is key to the evolution of the flow CIB Front Office businesses. The continuing process of standardized has created a tipping point for E-Trading in Fixed Income to grow tremendously in the coming decade - just as the period 2000-2010 saw a rapid move to electronic trading in equity markets globally. The Strats group as a whole combines expertise in quantitative analytics with a deep understanding of system architecture and programming to provide the key building blocks for algorithmic trading development. Within Strats, the Rates E-Trading group delivers an efficient client trading model and a low-latency interdealer hedging operation. The larger Strats group is also responsible for a scalable and flexible Front Office pricing and risk management system. The integration of these operations ensures an easy route to consistent analytic results and minimises duplication of equivalent technologies.
ETrading algorithms are under increasing pressure to perform. As the business migrates away from voice then the sensitivity to downtime increases. When downtime has a larger effect on the bottom line then the trading desk is more dependent on it. As the human trader gradually steps back from direct conversation with the client then the regulatory regime concentrates on the process that takes its place.
- Strong analytical and quantitative skills.
- Strong Object Oriented Programming skills – ideally with extensive Java experience:
- Data structures (maps, lists, vectors, queues) and use cases.
- Design patterns (factory, builder, adaptor, iterator, listener, producer/consumer, lambda functions, etc.).
- Object oriented programming (polymorphism, interfaces).
- Uses of singletons, static, global variables, const and immutability concepts.
- Intuition to seek out the edge case that will break an otherwise well designed algorithm.
- Patience to work through the available evidence to identify cause from effect.
- Educational background from a Tier-1 institution (Computer Science / Mathematics / Statistics / Engineering / Physics ).
Candidates are would also benefit from any combination of the following
- Coding in Python .
- KDB/Q experience.
- Experience in Financial Markets.
- Track record of developing of Algorithmic Trading tools.