Quant jobs / Squarepoint Capital

Junior Quant Researcher – ML Alpha Research

A junior research role applying time-series methods, machine learning and NLP to find trading signals at Squarepoint. You also help build ML tools used across the firm.

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.

Explore new datasets for predictive signals
Test time-series, ML and NLP techniques on trading data
Present research results to other researchers
Deploy and monitor models that feed trading signals

What they ask for

Required

Master's or higher in CS, ML/NLP, statistics, signal processing, optimisation or maths
Rigorous research ability
Programming in Python or kdb/q
Communication across regions
Delivering projects to tight timelines

Education: Master's or higher in computer science, ML/NLP, statistics, signal processing, optimisation, maths or related STEM subjects.
Experience: Junior; research ability matters more than years.
Languages and tools: Python
KDB+/q

How to prepare

Run an ML alpha project on public data with careful validation
Revise time-series methods and regularised regression
Try a finance NLP task such as news or filings sentiment
Study backtest overfitting and leakage

What to study

The NLP and ML Quant 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.