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Squarepoint Capital

Manages quant-driven, systematic portfolios globally

Junior Quant Developer

Quantitative DevelopmentConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • Degree in Applied Math, Physics, Engineering, Quantitative Finance, Computer Science or other quantitative disciplines
  • Up to 4 years of experience in a relevant role such as software or quant development
  • Proficiency in at least one of Python, C++, or KDB+/q
  • Strong interest in, or knowledge of finance and the global markets
  • Ability to work effectively with AI tools and systems, including demonstrable experience using them collaboratively to enhance software development, data analysis, or research workflows
  • Experience working with git and Linux
  • Excellent written and verbal communication skills
  • Eagerness to continuously learn new technologies and develop with us
  • Ability to work well in a fast-paced environment

Responsibilities

  • Develop tools to apply advanced statistical methods in order to identify new trading opportunities and to monitor their impact over time
  • Develop improvements to trading strategies through the running and thorough analysis of backtesting simulations across vast amounts of proprietary data
  • Drive cross-team initiatives at Squarepoint and work towards continued innovation in the quant research space

Desired Qualifications

  • Master's degree or higher with emphasis in a highly quantitative discipline
  • Deep knowledge of financial markets in at least one domain or asset class
  • Experience with database management systems and related technologies such as SQL
  • Experience working with financial data in a similar role

About the Company

Squarepoint Capital

Manages quant-driven, systematic portfolios globally

Squarepoint Capital is a global investment manager that uses quantitative and systematic strategies to build diversified portfolios across asset classes, trading frequencies, and global markets for institutional investors. Its approach relies on a large data platform and advanced technology to power research and model-based trading decisions, with portfolios continually adjusted in response to market data. The firm differentiates itself through a broad, multi-asset, multi-frequency framework, a global footprint with offices in thirteen cities, and a collaborative culture that emphasizes rigorous research and disciplined execution. Its goal is to deliver attractive, risk-aware returns for pension funds, endowments, and sovereign wealth funds through systematic, data-driven investment processes.

Company size
501-1,000
Company stage
Not listed
Total funding
$1.4B
Headquarters
London, United Kingdom
Founded
2014

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