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Salary
≈ $81k – $155k per year (Estimated)
Location
In office (London)
Visa
Licensed UK visa sponsor

Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Dec 2, 2024. Point72 scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Point72 is an American investment firm founded in 2014 when Steven Cohen converted his former hedge fund SAC Capital into a family office, before reopening to outside capital in 2018. It runs a multi-strategy business dominated by discretionary long and short equity teams organised as independent portfolio managers, alongside macro, systematic and quantitative strategies that rely heavily on alternative data and machine learning. Headquartered in Stamford, Connecticut with offices across North America, Europe and Asia, it also operates Point72 Ventures as a venture capital arm and runs a well-known academy programme that trains analysts from outside finance.

About Cubist

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

Role:

A new Cubist portfolio management team specializing in the systematic trading of equities is looking for a Quant Researcher whose core focus will be working on mid-frequency alpha strategies. Joining the team will provide a unique opportunity to be involved with the early stages of a product launch and develop within a growing team.

Responsibilities:

  • Perform rigorous and innovative research to discover systematic anomalies in the equities market
  • End-to-end development, including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation
  • Identify and evaluate new datasets for stock return prediction
  • Maintain and improve portfolio trading in a production environment
  • Contribute to the analysis framework for scalable research

Requirements:

  • MS or PhD in a quantitative discipline
  • 0-2 years of professional work experience
  • A background in financial markets is not necessary, but an interest in the field is essential
  • Proven expertise in Python and handling large datasets
  • Fluency in data science practices, e.g., feature engineering. Experience with machine learning is a plus
  • Highly motivated, curious, and critical thinker
  • Collaborative mindset with strong independent research abilities
  • Commitment to the highest ethical standards
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