Quantitative Developer - London- Prop Market Maker Quantitative Developer - London- Prop Market Maker …

Oxford Knight
in London, United Kingdom
Permanent, Full time
Last application, 24 Feb 21
Competitive
Oxford Knight
in London, United Kingdom
Permanent, Full time
Last application, 24 Feb 21
Competitive
Quantitative Developer - London
Summary:

An elite prop trading firm with a relaxed yet rewarding approach is looking for talented quantitative developers with Python experience. They are scientific, tech-driven and they invest heavily in their engineering teams. Developers here are truly world-class.

Working closely with Portfolio Managers and Researchers, you will be pivotal in the development of their systematic trading business. This is a high-impact role, responsible for deploying scalable and performant tools for research on large data sets, implementing advanced statistical techniques, and creating a market-leading research platform.

The ideal candidate will come from a mathematical background, with an enthusiasm for learning new technologies. You must be an exceptional communicator and be keen to share your expertise with end users to improve the standard of their Python engineering.

Requirements:
  • Strong Python experience, including writing, deploying and maintaining Python in a production environment
  • Sound programming fundamentals and mathematical techniques
  • Experience in any of the following is a bonus: large data sets, time series, Python libraries (sciPy, numPy, pyTorch, etc.), knowledge of financial markets
  • Outstanding level of attention to detail and quality

Culture / Benefits
  • Excellent bonus potential and compensation
  • Friendly, informal yet highly rewarding work culture
  • No dress code, catered offices and regular social events
  • Work with the latest technologies on complex problems with significant impact


Contact
If you feel you are a good match, please don't hesitate to get in touch:

Dan Hampton
dan.hampton@oxfordknight.co.uk
linkedin.com/in/dan-hampton-ab029392

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