Quant jobs / Jane Street

Machine Learning Researcher Internship

A research internship working with Jane Street's ML researchers on projects tied to systematic trading. Interns learn how the firm thinks about markets and train practical 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.

Run an end-to-end study of an unexplored dataset
Try a new modelling approach on a hard prediction problem
Tune hyperparameters and debug training issues
Analyse your model's predictions on market data

What they ask for

Required

Undergraduate, PhD student or postdoc
Practical ML experience
Logical and mathematical thinking
Python and an ML framework
Breadth across model types
English fluency

Education: Current undergraduate, PhD student or postdoc.
Experience: Students with practical ML project experience
Languages and tools: Python

How to prepare

Complete an end-to-end ML project on a noisy time series dataset
Learn why non-stationarity breaks naive validation
Practise implementing and iterating on models quickly in Python
Study time series cross-validation 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 Jane Street’s site before applying: requirements, location and pay can change after we check them.

View the posting on Jane Street’s site ↗

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