Quant jobs / Trexquant

Quantitative Researcher - Experienced Hires (USA)

This researcher develops systematic signals using statistical and machine-learning methods. Current hiring interests include equity, futures, commodity and event-driven strategies.

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.

Investigate predictive features in large financial datasets
Implement research ideas and validate them through simulations
Add new data sources to existing forecasting models
Review strategy robustness with fellow researchers

What they ask for

Required

Systematic-trading research experience
Python
Machine-learning interest
Quantitative problem-solving
Team-based research

Education: STEM qualification at bachelor, master or doctoral level.
Experience: 2+ years conducting systematic trading work.
Languages and tools: Python
Markets: equities, futures, commodities

How to prepare

Prepare a research case that separates development and evaluation data
Show the incremental value of a new dataset
Explain a failed signal and the evidence behind rejecting it

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.