Quantitative Researcher
A research role on the team behind a firm's automated electronic trading strategies. You develop predictive signals and models and own them from hypothesis to production.
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.
- Develop predictive signals for automated trading strategies
- Improve strategy PnL through iteration on existing models
- Apply statistics and ML to noisy market data
- Carry ideas through to production and monitor their results
What they ask for
Required
- Interest or experience in systematic trading
- Statistics and ML on noisy real-world data
- Software development in Java, C++ or Python
- Drive to deliver scalable, maintainable strategies
- Collaboration and independence
- Education
- No degree level stated
- Experience
- Experienced hires; new graduates have a separate posting
- Languages and tools
How to prepare
- Build and validate a predictive signal on noisy data, controlling for overfitting
- Practise ML on small-signal datasets, including regularisation and cross-validation
- Write clean, efficient Python or C++ for research
- Study how a signal becomes a traded strategy, with costs and capacity
What to study
- Quantitative Research, Data and Backtesting
- Financial Machine Learning
- Probability, Statistics and Financial Data
- Python for Quantitative Finance
The HFT 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 Headlands Technologies’s site before applying: requirements, location and pay can change after we check them.
View the posting on Headlands Technologies’s site ↗
SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Headlands Technologies and doesn’t handle applications.