Intraday Quant Researcher: Create High-Return Trading Models

Durlston Partners; England; On-site; GBP 90,000 - 160,000; Full time

Job summary

Durlston Partners is seeking a highly talented Quantitative Researcher to join a research-focused systematic trading team developing mid-frequency, intraday strategies across a broad range of asset classes.

The team prioritizes researchers with a strong track record of Sharpe ratios above 2, from idea generation through backtesting to production. This role offers ownership over research in a collaborative, technically demanding environment.

Qualifications

• 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; Sharpe ratios >2 desirable.
• Excellent Python skills and strong quantitative programming ability.
• Experience with large datasets and rigorous empirical research.
• 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 considered if outstanding technical ability and academic pedigree.

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

Skills

Python

Quantitative research

Time-series

Statistics

Machine Learning

Deep Learning

Derivatives

Mathematics

Education

Quantitative degree

Tools

Python

Pandas

NumPy

Backtesting

Job description

Durlston Partners is seeking a highly talented Quantitative Researcher to join a research-focused systematic trading team developing mid-frequency, intraday strategies across a broad range of asset classes.

The team prioritizes researchers with a strong track record of Sharpe ratios above 2, from idea generation through backtesting to production. This role offers ownership over research in a collaborative, technically demanding environment.