Full-Time

Junior Quant Researcher

ML Alpha Research

Confirmed live in the last 24 hours

Squarepoint Capital

Squarepoint Capital

501-1,000 employees

Global investment manager specializing in quantitative strategies

Quantitative Finance
Financial Services

Compensation Overview

$60kAnnually

+ Discretionary Bonuses

Entry, Junior

Boston, MA, USA + 2 more

More locations: London, UK | New York, NY, USA

Category
Quantitative Research
Quantitative Finance
Required Skills
Python
Natural Language Processing (NLP)
Data Analysis
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.

Squarepoint Capital specializes in managing investments using quantitative and systematic strategies. The firm builds diversified portfolios that span various asset classes and trading frequencies across global markets. By leveraging advanced technology and a comprehensive data platform, Squarepoint Capital makes informed investment decisions based on thorough research, aiming to deliver strong returns for its clients. Unlike many competitors, Squarepoint Capital focuses on systematic trading and data-driven approaches, which allows for a more structured investment process. The company's goal is to provide high-quality returns to a diverse range of institutional investors, including pension funds and sovereign wealth funds, while fostering a collaborative work environment that promotes continuous learning and professional development.

Company Stage

N/A

Total Funding

$1.1B

Headquarters

London, United Kingdom

Founded

2014

Simplify Jobs

Simplify's Take

What believers are saying

  • Squarepoint's diverse portfolio reduces risk and increases potential for high returns across various sectors.
  • The firm's commitment to quantitative research and data-driven strategies can lead to more informed and potentially profitable investment decisions.
  • Hiring experienced professionals from other hedge funds can bring fresh perspectives and innovative strategies to the firm.

What critics are saying

  • The broad investment approach may spread resources too thin, potentially impacting the depth of analysis and performance.
  • Relying heavily on quantitative research could lead to significant losses if the models fail to predict market movements accurately.

What makes Squarepoint Capital unique

  • Squarepoint Capital's strategy of acquiring stakes in a diverse range of companies, from tech to healthcare, showcases its broad investment approach.
  • The firm's focus on quantitative research and hiring talent from other hedge funds, like Romain Colas from Ovata Capital, highlights its commitment to data-driven investment strategies.
  • Squarepoint's ability to identify and invest in emerging companies, such as Cipher Mining and aTyr Pharma, sets it apart from more conservative investment firms.

Help us improve and share your feedback! Did you find this helpful?