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Squarepoint Capital

Manages quant-driven, systematic portfolios globally

Junior Quant Researcher - Machine Learning Alpha Research

Quantitative ResearchConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • Quantitative background - includes advanced degrees in computer science, machine learning / NLP, statistics, signal processing, optimization, mathematics and related STEM subjects (masters or higher)
  • Demonstrated ability for doing high quality and rigorous research, along with communicating results to stakeholders.
  • Programming proficiency with at least one major programming or scripting language (e.g. python, kdb-q)
  • Strong communication skills and ability to work well with colleagues across multiple regions
  • Ability to work well in collaborative and high pace settings, and drive projects to completion in accelerated timelines.

Responsibilities

  • Research statistical techniques such as time-series methods, machine learning and NLP to extract value from data
  • Analyze large data sets using advanced statistical and ML methods to identify trading opportunities
  • Help to develop statistical and ML based tools and techniques to solve complex data related problems throughout the firm.
  • Primary focus throughout the day is on researching new statistical and ML techniques and exploring datasets
  • Discuss and present research results with other researchers
  • Deploy and monitor models used to generate trading signals.

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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