Quant jobs / WorldQuant

Data Science Intern

A research internship applying machine learning to financial and unstructured data to build predictive datasets. It comes with one-to-one mentoring and no finance experience is required.

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.

Model financial datasets with machine learning methods
Check the quality of unstructured data and extract useful signals
Build datasets intended to predict market movement
Learn finance while working with a mentor

What they ask for

Required

Studying for a Master's or PhD in a quantitative field
At least one programming language (C++, Python)
Linux/Unix familiarity
English reading and writing
Interest in financial markets

Preferred

Deep learning, NLP or LLM research experience

Education: Currently pursuing a Master's or PhD in a related field such as physics, CS, maths or financial engineering
Experience: Internship; no finance experience required
Languages and tools: Python
C++

How to prepare

Train and evaluate a machine learning model on a financial time series
Practise cleaning and validating text or alternative data
Get comfortable with the Linux command line
Read introductory material on NLP for finance

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

View the posting on WorldQuant’s site ↗

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