Quantitative Equity Researcher Systematic Strategies - London

We are working with a leading global asset manager with a well-established systematic equities platform, currently expanding its research group due to sustained growth across its quantitative strategies. The team runs a broad range of rules-based and factor-driven portfolios across regions, styles, and risk profiles, and is continuing to invest in research, data, and technology to support new product development and AUM growth.

They are seeking a Quantitative Equity Researcher to contribute to the design, testing, and implementation of equity signals, support portfolio construction, and monitoring, and help evolve the firm’s research and production infrastructure.

Key Responsibilities

• • Research and develop cross-sectional equity alpha and risk factors, including style and thematic signals.
  • Perform back-testing, validation, performance attribution, and risk analysis across systematic strategies.
  • Contribute to portfolio construction, rebalancing frameworks, and optimisation techniques.
  • Work with large structured and unstructured datasets, including alternative data, and apply machine learning or NLP techniques where relevant to enhance signal generation.
  • Build and maintain Python-based research and production pipelines, collaborating closely with engineering teams to deploy models into live trading and reporting environments.
  • Produce clear research documentation and present results to portfolio managers, senior stakeholders, and, where required, clients.

Required Background

• • Several years’ experience in quantitative research within systematic equities, asset management, or a closely related environment.
  • Strong programming skills in Python, with experience using SQL and modern data science libraries.
  • Solid foundation in statistics, machine learning, and optimisation techniques.
  • Experience with factor models, return attribution, and empirical asset pricing research.
  • Advanced degree (PhD or MSc) in a highly quantitative field such as Mathematics, Statistics, Physics, Engineering, Computer Science, or Econometrics.
  • Ability to communicate complex quantitative concepts clearly to both technical and non-technical audiences.

To apply, please send a copy of your CV in a word format to

mailto:[email protected]