Durlston Partners
Quantitative Researcher
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High-Frequency Quantitative Researcher
The Role
We are looking for an exceptional Quantitative Researcher to join a highly technical Research team focused on developing high-frequency, short-horizon systematic trading strategies.
The role will involve researching signals and predictive models at very short time horizons, exploiting market microstructure, order-book dynamics, and other sources of high-frequency alpha. Researchers will have significant ownership of the full research lifecycle, from idea generation and data analysis through to backtesting, optimisation, and production deployment.
The team typically consists of around 8 researchers, providing a collaborative but highly intellectually demanding environment.
Responsibilities
- Research and develop high-frequency systematic trading strategies
- Identify and validate short-horizon sources of alpha using market data and quantitative techniques
- Analyse order-book dynamics, market microstructure, execution, and trading behaviour
- Develop predictive signals, statistical models, and quantitative strategies
- Work with large-scale, high-frequency datasets and conduct rigorous empirical analysis
- Build and improve research and backtesting infrastructure
- Optimise strategies for robustness, scalability, and transaction costs
- Collaborate closely with traders, quantitative researchers, and engineers to take strategies into production
- Analyse live strategy performance and continuously identify opportunities for improvement
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Requirements
- Exceptional academic background in Mathematics, Statistics, Computer Science, Physics, Engineering, or another highly quantitative discipline
- Proven experience in quantitative research within HFT, proprietary trading, or systematic investment
- Strong understanding of statistics, probability, time-series modelling, and quantitative research methodologies
- Experience researching short-horizon or high-frequency strategies
- Strong knowledge of market microstructure and financial market data
- Excellent Python skills and strong programming ability; C++ experience is highly desirable
- Demonstrable track record of developing profitable systematic signals and strategies
- Strong analytical and problem-solving ability
Desirable
- Experience across multiple asset classes; derivatives experience is particularly relevant
- Experience with order-book data, tick data, and event-driven datasets
- Strong understanding of execution, transaction costs, and market impact
- Experience with Machine Learning / Deep Learning
- Competitive background in mathematics, programming, physics, or quantitative competitions
- Experience at a research-heavy HFT or systematic trading firm
- Exceptional candidates from non-traditional backgrounds with outstanding mathematical and technical ability will also be considered
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What We're Looking For
We are looking for exceptionally strong quantitative researchers, rather than candidates who simply match a conventional HFT checklist.
Candidates from leading HFT and systematic trading firms are of particular interest, but we are also open to researchers from less traditional environments who demonstrate exceptional mathematical ability, programming skills, academic credentials, or competitive achievements.
The ideal candidate will have a deep curiosity for markets, an extremely rigorous research mindset, and the ability to extract signal from noisy, high-dimensional datasets at very short time horizons.
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