KDB / Python Lead Quant Developer - Systematic Equities London/Dubai- Leading Multi-Strategy IM
  • England,London
  • full-time
  • Competitive salary
Job Description:
Salary: 200-600k GBP TC

Summary:

One of the world’s most prestigious hedge funds is looking for a Quant Developer to be a founding member of one of their high-frequency systematic equities pods. This is a high impact role, within a small, entrepreneurial team, where you will develop systematic backtesting, visualization/analyzing and a trading platform for global equity strategies.

To do this, you’ll collaborate with the senior PM and the team, implementing an efficient backtester tool for both simulation and live trading. You’ll also design and implement trading systems, ensuring reliability, scalability, and timely execution, as well as sharing knowledge and promoting best practices in mentorship to junior developers.

The successful Quant Developer will be a fantastic problem-solver with strong analytical skills, with the ability to quickly understand and apply complex concepts.

Skills and Experience Required:
*3-5+ years’ experience in developing algorithmic trading systems, preferably in systematic equity trading markets
*Substantial KDB/Q and Python programming experience
*Good knowledge of modern data science tools stacks, e.g. Jupyter, pandas, numpy, sklearn, with ML experience
*Bachelors or Masters degree in Computer Science, Mathematics, Statistics, or related STEM field from a top-tier university
*Good understanding of using Slurm or similar parallel computing tools

Benefits & Incentives:
*Significant salary + bonus + benefits
*Dynamic, fast-paced environment; excellent career growth opportunities
*Collaborative culture and an energetic, dynamic engineering atmosphere
*Build and share knowledge with the smartest engineers in the industry


Contact
If you think you are a good fit for the role and would like further information, please contact:

Dominic Copsey

+44 (0)
in/dom-copsey-586478143/
Job number 1727651
metapel
Company Details:
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