High-Frequency Quant Researcher: Signals & Microstructure

Durlston Partners; England; On-site; GBP 110,000 - 190,000; Full time

Job summary

Durlston Partners is seeking an exceptional Quantitative Researcher to join a highly technical Research team focused on developing high-frequency, short-horizon systematic trading strategies.

The role involves researching signals and predictive models at very short time horizons, analysing market microstructure, backtesting and production deployment, with an emphasis on robustness and low transaction costs.

Qualifications

• Exceptional academic background in quantitative disciplines.
• 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.
• 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

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

Skills

Mathematics

Statistics

Computer Science

Physics

Engineering

Python

C++

Education

Quantitative degree

Tools

Python

C++

Job description

Durlston Partners is seeking an exceptional Quantitative Researcher to join a highly technical Research team focused on developing high-frequency, short-horizon systematic trading strategies.

The role involves researching signals and predictive models at very short time horizons, analysing market microstructure, backtesting and production deployment, with an emphasis on robustness and low transaction costs.