Quantitative Researcher (Optimisation)

Thurn Partners; England; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading equity strategy firm in the United Kingdom is seeking a quantitative researcher to advance its portfolio optimisation capabilities. You will enhance frameworks for systematic equity portfolios, lead alpha research, and implement robust risk models. Ideal candidates have a strong background in statistics and programming (Python), as well as a Master's or PhD in a relevant quantitative field. This role offers an outstanding opportunity to collaborate in a dynamic, research-focused environment.

Qualifications

• Must have an MSc or PhD in mathematics, statistics, machine learning, physics, or engineering.
• Strong foundation in statistics and equity market microstructure is essential.
• Advanced programming skills in Python are required.

Responsibilities

• Develop and enhance portfolio optimisation frameworks.
• Perform alpha research to generate predictive equity signals.
• Design and implement risk models and factor constraints.
• Integrate alpha forecasts and risk estimates into optimisation pipelines.
• Research on turnover and execution-aware portfolio construction.
• Collaborate to deploy strategies into live trading.

Skills

Statistics

Optimisation

Python

Quantitative research

Education

MSc or PhD in a quantitative discipline

Job description

Company: Globally leading, fully systematic equity stat‑arb business.

Location: London, United Kingdom.

Brief: The firm's specialist portfolio optimisation and construction team is seeking an additional researcher to expand its optimisation and alpha research capabilities.

Responsibilities:

• Develop and enhance portfolio optimisation and construction frameworks for systematic equity portfolios.
• Perform alpha research to generate, test, and productionise predictive equity signals and strategies.
• Design and implement risk models and factor constraints.
• Integrate alpha forecasts, risk estimates, and liquidity constraints into scalable optimisation pipelines.
• Research on turnover, capacity, and execution‑aware portfolio construction.
• Work collaboratively across the firm to deploy strategies into live trading.

Requirements:

• MSc or PhD in a quantitative discipline (mathematics, statistics, machine learning, physics, engineering).
• Strong foundation in statistics, optimisation, and equity market microstructure.
• Advanced programming skills in Python.
• Prior experience in buy‑side quant research across systematic equities.