London Stock Exchange · Posted 1d ago
Senior Analyst (Quant Research)
Job relayed by Stapply Data, its source: you apply there.
- Location
- 🇬🇧 London, United Kingdom
- Contract
- Full-time
- Role
- Data science
- Source
- Stapply Data
Stack
- Pandas
- NumPy
- LLM
- SQL
- Python
- CI/CD
The posting
Join our team as a Senior Analyst in Quantitative Research & Development. This hands-on role requires a highly technical and versatile individual who enjoys solving problems across quantitative development, data analysis, research, and operational delivery. You will take ownership of problems from investigation through resolution and work across multiple teams and disciplines. Key responsibilities include developing and maintaining Python and SQL-based research tools, performing detailed data analysis and validation, developing automation and AI-enabled tools, and supporting quantitative investment and index research. The ideal candidate will have approximately 5 years of experience in quantitative development, financial data analytics, or a related discipline, with strong hands-on Python and SQL skills.
- Develop, test, and maintain Python and SQL-based research tools, investment analytics, and data pipelines. - Perform detailed data analysis, validation, and quality assurance across large financial datasets; investigate anomalies and identify root causes. - Support quantitative investment and index research, including factor analysis, regression, portfolio optimisation, risk modelling, and performance analytics.
- Above all, we are looking for an agile, curious and highly motivated problem solver who pays meticulous attention to detail, learns quickly, takes ownership and is comfortable juggling multiple priorities in an environment where the skills required can change from one task to the next - The ideal candidate will have approximately 5 years of experience in quantitative development, financial data analytics, quantitative research or a related discipline, with strong hands-on Python and SQL skills - Candidates should have a good understanding of equity markets and quantitative techniques such as regression, optimisation, factor investing and risk modelling, combined with a rigorous approach to financial data and quality assurance - Experience with pandas, NumPy, Git, testing, CI/CD, cloud computing and modern development environments such as VS Code and GitHub Copilot is highly desirable, as is practical experience developing with generative AI and AI agents