Squarepoint Capital

Desk Quant Analyst

Squarepoint Capital · London, UK
London, UK Posted 2026-08-06
Type
Full-time
Experience
0-2 yr

Please only apply to the one job you feel best fits your skillset and experience. If our team feels you are better suited for another role, we will reach out about the alternate opportunity.

Position Overview:

We are looking for highly motivated graduates or early career professionals with an interest in finance and a background in computer science, engineering, mathematics or other STEM degrees to join our Desk Quant Analyst role.

In this role, you will:

  • Maintain and upgrade the codebase and configuration of strategies within the firm’s automated trading framework.
  • Manage large datasets used in both research and production environments.
  • Perform live as well as historical monitoring of trading activities.
  • Work in close collaboration with experienced Quantitative Researchers and Traders to understand the constantly evolving needs of the trading desks.

Typical Day of Desk Quant Analyst:

  • Before market open, check that all required data and related processes are ready for the trading day.
  • During market hours, sporadically monitor behavior and performance of strategies.
  • Work on various longer-term projects required for expanding our systematic trading activities and ensuring their robustness.

Required Qualifications :

  • Degree in Engineering, Computer Science or related technical subject.
  • Programming proficiency with at least one major programming or scripting language (e.g. C++, Java, Python).
  • Great attention to detail.
  • Strong communication skills and ability to work well with colleagues across multiple regions.
  • Ability to work well under pressure.

Nice to have:

  • Knowledge of Q/KDB+.
  • Knowledge of Linux and Bash.
  • Advanced quantitative skills.

#LI-DNP

JavaPythonC++
Squarepoint Capital

Squarepoint Capital

Quantitative Trading · Private · New York City, USA

Stage & Valuation
Private · $182B
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Squarepoint Capital operates as a global quantitative investment management firm that develops and executes algorithmic trading strategies across multiple asset classes and markets. The firm leverages mathematical models, statistical arbitrage, and machine learning to systematically invest in financial markets worldwide.
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