Algorithm Developer (Quant Research & Trading) – 2027 Grads
A graduate role building the models that drive HRT's trading, working with other algorithm developers and software engineers. Work covers predictive models, execution methods and live performance monitoring.
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.
- Analyse large market datasets to build predictive models
- Test new order execution and model training methods
- Run models live and review daily performance
- Work with engineers on high-performance trading infrastructure
What they ask for
Required
- Full-time undergraduate or master's student in a quantitative subject
- Python and/or C++
- Statistics, numerical programming or ML
- Strong analytical and problem-solving
- Ability to work independently on long problems
- Education
- Undergraduate or master's student in maths, physics, computer science, statistics or similar.
- Experience
- Students eligible for full-time roles in 2027
- Languages and tools
- Markets
- multi-asset
How to prepare
- Build and test a predictive model on public price data with honest out-of-sample validation
- Practise statistics and probability problems
- Become fluent in pandas and NumPy
- Learn the basics of C++ for performance-sensitive code
What to study
- Probability, Statistics and Financial Data
- Python for Quantitative Finance
- Quantitative Research, Data and Backtesting
- Econometrics and Financial Time Series
- Modern C++ for Quantitative Finance
The Quantitative Researcher roadmap sets out the stages for this kind of role, with free resources for each.
Open the roadmapApply
Read the full posting on Hudson River Trading’s site before applying: requirements, location and pay can change after we check them.
View the posting on Hudson River Trading’s site ↗
SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Hudson River Trading and doesn’t handle applications.