Durlston Partners
Quantitative Researcher
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Mid-Frequency Quantitative Researcher
The Role
We are looking for a highly talented Quantitative Researcher to join a research-focused systematic trading team developing mid-frequency, intraday trading strategies across a broad range of asset classes.
The team is particularly interested in researchers with a strong track record of developing systematic strategies with Sharpe ratios above 2, from idea generation and statistical research through to backtesting and production implementation.
There is no specific asset-class requirement. Experience across multiple markets is highly valued, with the majority of the team's trading focused on derivatives.
You will join a close-knit Research team of approximately 8 researchers, working in a highly technical and intellectually demanding environment with significant ownership over your research.
Responsibilities
- Research and develop systematic intraday and mid-frequency trading strategies
- Identify new sources of alpha through statistical analysis, quantitative modelling and rigorous hypothesis testing
- Develop and improve signals, forecasting models and portfolio construction techniques
- Conduct large-scale analysis of market and alternative datasets
- Build robust backtesting frameworks and evaluate strategies across different market regimes
- Work closely with other researchers and traders to translate research ideas into production strategies
- Continuously monitor and improve live strategies through performance analysis and further research
- Apply strong statistical and mathematical thinking to problems across different asset classes
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Requirements
- Strong academic background in Mathematics, Statistics, Computer Science, Physics, Engineering, Economics or a related quantitative discipline
- Proven experience in quantitative research within systematic trading
- Strong understanding of statistical modelling, time-series analysis, probability and optimisation
- Experience researching intraday / mid-frequency strategies
- Demonstrable ability to develop strategies with strong risk-adjusted returns; experience with Sharpe ratios >2 is highly desirable
- Excellent Python skills and strong quantitative programming ability
- Experience working with large datasets and conducting rigorous empirical research
- Strong problem-solving ability and a genuine interest in financial markets
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Desirable
- Experience across multiple asset classes, particularly derivatives
- Experience with Machine Learning / Deep Learning techniques
- Strong competitive background in mathematics, programming or quantitative competitions
- Experience at a research-intensive hedge fund, proprietary trading firm or systematic investment manager
- Exceptional candidates from non-traditional backgrounds will also be considered where they demonstrate outstanding technical ability and academic pedigree
What We're Looking For
We are particularly interested in exceptionally strong researchers rather than candidates who simply match a conventional checklist.
Candidates from research-heavy systematic trading firms are of particular interest, but we are equally open to individuals from less traditional environments who combine outstanding education, mathematical ability, coding skills and evidence of exceptional quantitative problem-solving.
The ideal candidate will be intellectually curious, highly rigorous and comfortable taking a research problem from an initial hypothesis through to a robust, statistically validated trading strategy.
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