Quantitative Equity Researcher - Systematic Strategies - London
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Added before 5 Days
- England,London,City of London
- Full Time, Permanent
- Competitive salary
Job Description:
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:
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:
Job number 3455086
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