# Quantitative Researcher at Point72

> United Kingdom · Unspecified · Other · open. Source: https://alderhq.app/jobs/greenhouse%3Apoint72%3A7752293002 (read 2026-11-06).

## Facts (observed)

- Company: [Point72](https://alderhq.app/companies/point72)
- Location text: London ; UK
- Where it can be done from (inferred): United Kingdom (evidence: "Location: London ; UK")
- Posted: 2024-12-02 (704 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://boards.greenhouse.io/point72/jobs/7752293002?gh_jid=7752293002
- Skills listed (inferred): Python

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (London, n 1852): p25 £45k, median £57k, p75 £73k
- H-1B filings at this company for similar roles, FY26: 11, median offered wage $300k ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance))

## Description (the employer's text)

### 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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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Apoint72%3A7752293002 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.