Quant jobs / Two Sigma

Quantitative Researcher – Machine Learning

A researcher role focused on machine learning for investment models across global markets at a quantitative investment firm. It stresses understanding algorithms deeply enough to adapt them.

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.

Apply machine learning to a wide range of datasets for trading models
Adapt and tune algorithms to the problem
Test hypotheses with engineers
Follow and share research via reading circles and conferences

What they ask for

Required

Degree in statistics, maths, physics, electrical engineering or CS
Intermediate skills in a language such as Python or C++
Deep understanding of machine learning algorithms
Applied machine learning on real-world data
Published or presented work

Education: Degree in a technical or quantitative discipline; all levels from bachelor's to doctorate welcome.
Experience: Applied machine learning experience; years not stated
Languages and tools: Python
C++
Java
C

How to prepare

Implement a core ML algorithm from scratch and modify it for a new loss or constraint
Run an applied ML project on noisy real data with rigorous validation
Learn time-series cross-validation and leakage avoidance
Write up and present your work as a paper or talk

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 Two Sigma’s site before applying: requirements, location and pay can change after we check them.

View the posting on Two Sigma’s site ↗

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