Algo Trader/Researcher

Job Title: Algo Trader/Researcher
Contract Type: Permanent
Location: London, England
Salary: bens
REF: ND386758_1524507737
Contact Name: Nick Derewlany
Contact Email:
Job Published: 9 months ago

Job Description

The firm is a proprietary trading organisation. It employs some of the most talented traders, developers and engineers in the market, executing a diverse range of strategies across global equity and derivatives markets. It is the most active participant in a number of the products it trades, contributing significant liquidity to many European markets. The company's culture is collaborative, informal and highly rewarding of strong performance.


The firm is looking for an algorithmic trader / researcher to join our expanding delta1 team. The team is responsible for the full trading stack. This includes everything beginning with raw market data and ending with trading revenue. This is an excellent opportunity for an experienced trader to add value in a successful team. This is a full-time, permanent position and will be based in London. Remuneration comprises of an annual base salary, benefits, and discretionary bonus.


  • Day to day responsibility of trading multiple strategies on multiple markets
  • Working with data to design and implement new trading strategies
  • Researching and back testing ideas for improving trading strategy performance
  • Rigorous risk management and perfect compliance with regulatory rules
  • Improving strategies through analysis, prototyping, and collaboration with developers



  • Degree or Masters equivalent to a 2:1 or above in a technical subject
  • Experience in writing, running, and analysing systematic trading strategies
  • Proactive interest in improving existing trading strategies and identifying new opportunities
  • Experience in a numerical programming language (Python, R, Matlab, Julia, etc.)
  • Outstanding analytical and statistical skills
  • Excellent attention to detail and fast problem solving skills
  • Enjoy working in a small and efficient team