Quant jobs / Squarepoint Capital

Quantitative Researcher – Equity Mid-Frequency

A mid-frequency equity researcher at Squarepoint building and validating systematic strategies. You use statistics and machine learning to find effects and improve live models.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Find and test new statistical effects in equity data
Analyse and improve behaviour of live strategies using KDB/q and Python
Validate trading simulations and applications
Research ways to reduce execution costs
Automate data dependency processes for strategies

What they ask for

Required

Master's in a quantitative field
2 years in quant research
Python and kdb/q
Regression, machine learning and inference
Backtesting and strategy deployment
Market structure and statistical arbitrage knowledge

Education: Master's or equivalent in statistics, data science, electrical engineering, physics, OR, maths, computer science, econometrics or related.
Experience: 2 years as a quant researcher or similar role in investment management.
Languages and tools: Python
KDB+/q
Shell
Excel/VBA
Markets: equities

How to prepare

Replicate an equity cross-sectional signal with realistic costs
Study statistical arbitrage and pairs methods
Practise KDB/q analysis on tick data
Learn robustness testing for backtests

What to study

The Quantitative Researcher roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on Squarepoint Capital’s site before applying: requirements, location and pay can change after we check them.

View the posting on Squarepoint Capital’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Squarepoint Capital and doesn’t handle applications.