Quantitative Researcher (Systematic Trading)

Bonhill Partners; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Bonhill Partners is seeking an experienced Equities Quantitative Researcher to join a high-performing research team focused on alpha signal research, portfolio construction, and systematic investment strategies. You will work with large datasets and world-class compute resources to take ideas from research to live implementation.

The role involves developing predictive alpha signals, testing strategies, and collaborating with Quant Developers and Portfolio Managers to productionise research.

Qualifications

• MSc or PhD in Mathematics, Statistics, Physics, Computer Science, Engineering, Machine Learning, Quantitative Finance, Economics (highly quantitative)
• Strong experience as a Quantitative Researcher within a similar environment
• Proven experience researching equity alpha signals
• Strong background in portfolio construction, portfolio optimisation, and portfolio structuring
• Experience developing systematic equity investment models
• Excellent understanding of: Cross-sectional factor models, Statistical arbitrage, Risk modelling, Optimisation techniques, Transaction cost modelling, Capacity analysis, Experience working with large financial datasets

Responsibilities

• Research and develop predictive alpha signals across global equity markets.
• Design, test, and improve systematic investment strategies using statistical and machine learning techniques.
• Build and enhance portfolio construction and optimisation models.
• Develop risk-aware portfolio structuring methodologies that maximise risk-adjusted returns.
• Analyse large alternative and traditional datasets to identify new investment opportunities.
• Evaluate signal robustness through extensive backtesting and out-of-sample validation.
• Work closely with Quant Developers and Portfolio Managers to productionise research.
• Improve research frameworks, data pipelines, and model performance.
• Monitor live strategy performance and continuously refine models.

Skills

Quantitative research

Backtesting

Collaboration

Education

MSc/PhD in Math/Stats/CS/Engineering/ML/Quant Finance

Tools

SQL

PyTorch or TensorFlow

Git

Job description

Our client is a leading systematic trading firm that leverages cutting-edge quantitative research, technology, and data science to develop scalable investment strategies across global equity markets.

They are looking to hire an experienced Equities Quantitative Researcher to join a high-performing research team focused on alpha signal research, portfolio construction, and systematic investment strategies. This is an opportunity to work alongside some of the industry's strongest quantitative minds, taking ownership of research that directly influences live trading portfolios.

You'll have access to extensive datasets, world-class compute infrastructure, and the freedom to develop innovative ideas from research through to implementation.

Responsibilities

• Research and develop predictive alpha signals across global equity markets.
• Design, test, and improve systematic investment strategies using statistical and machine learning techniques.
• Build and enhance portfolio construction and optimisation models.
• Develop risk-aware portfolio structuring methodologies that maximise risk-adjusted returns.
• Analyse large alternative and traditional datasets to identify new investment opportunities.
• Evaluate signal robustness through extensive backtesting and out-of-sample validation.
• Work closely with Quant Developers and Portfolio Managers to productionise research.
• Improve research frameworks, data pipelines, and model performance.
• Monitor live strategy performance and continuously refine models.

Required Experience

• MSc or PhD in one of the following: Mathematics, Statistics, Physics, Computer Science, Engineering, Machine Learning, Quantitative Finance, Economics (highly quantitative)
• Strong experience as a Quantitative Researcher within a similar environment.
• Proven experience researching equity alpha signals.
• Strong background in portfolio construction, portfolio optimisation, and portfolio structuring.
• Experience developing systematic equity investment models.
• Excellent understanding of: Cross-sectional factor models, Statistical arbitrage, Risk modelling, Optimisation techniques, Transaction cost modelling, Capacity analysis, Experience working with large financial datasets.

Technical Skills

• SQL
• PyTorch or TensorFlow (desirable)
• Git

Experience with cloud computing, distributed research environments, or high-performance computing would be advantageous.