Quant jobs / Trexquant

Quantitative Researcher - Early Career (USA)

This early-career role researches predictive models for Trexquant’s systematic portfolios. Researchers are matched to a signal, strategy or data-focused team during hiring.

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.

Transform financial datasets into candidate predictive features
Fit and evaluate statistical or machine-learning models
Replicate useful academic results and test new hypotheses
Compare model behaviour in trading simulations

What they ask for

Required

Python
Interest in machine learning
Quantitative problem-solving
Independent and collaborative research

Preferred

Financial-accounting knowledge
Quant-finance background

Education: Bachelor or postgraduate qualification in a STEM subject.
Experience: Early-career applicants; no minimum number of years is stated.
Languages and tools: Python
Markets: equities, futures

How to prepare

Build a time-ordered research experiment in Python
Compare a simple baseline with a machine-learning forecast
Document how feature availability and overfitting affect simulated results

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

View the posting on Trexquant’s site ↗

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