Senior Analyst (Quant Research)

London Stock Exchange; Greater London; Sur place; GBP 120 000 - 180 000; Plein temps

Résumé du poste

London Stock Exchange seeks a highly technical Senior Analyst, Quantitative Research & Development to solve problems across development, data analysis, research and delivery. You will own problems from investigation through resolution while working across multiple teams and disciplines.

Responsibilities include developing Python/SQL tools, validating analytics, and building AI-enabled automation for research and operations. Strong knowledge of equity markets and QA culture is essential.

Qualifications

• 5 years of experience in quantitative development, financial data analytics or related field.
• Strong hands-on Python and SQL skills.
• Good understanding of equity markets and quantitative techniques (regression, optimisation, factor investing, risk modelling).
• Rigorous approach to financial data and QA; experience with pandas, NumPy, Git, testing, CI/CD, cloud computing.

Responsabilités

• Develop, test and maintain Python and SQL‑based research tools, analytics and data pipelines.
• Perform data analysis, validation and QA across large financial datasets; investigate anomalies.
• Develop automation and AI-enabled tools to improve research and operational workflows.
• Support index research, methodology development and rebalances; assist client-facing analyses.
• Collaborate with Research, Engineering and Data Operations to translate requirements into scalable solutions.

Connaissances

Python

SQL

Data analysis

Pandas

NumPy

Git

CI/CD

Cloud computing

Generative AI

AI agents

Outils

Worldscope

IBES

Lipper

Datastream

Refinitiv Workspace

Description du poste

• We are seeking a highly technical and versatile Senior Analyst, Quantitative Research & Development who enjoys solving problems across quantitative development, data analysis, research and operational delivery
• This is a hands-on role requiring the ability to switch rapidly between priorities: one day developing a Python research tool or AI-enabled workflow, another investigating a complex data issue, validating investment analytics or supporting a research or client request
• The successful candidate will take ownership of problems from investigation through resolution and be comfortable working across multiple teams and disciplines
• Develop, test and maintain Python and SQL-based research tools, investment analytics and data pipelines, applying strong software engineering and CI/CD practices
• Perform detailed data analysis, validation and quality assurance across large financial datasets; investigate anomalies and identify root causes across data, code and methodology
• Develop automation and AI-enabled tools and agents to improve research, data checking and operational workflows
• Support quantitative investment and index research, including factor analysis, regression, portfolio optimisation, risk modelling and performance analytics
• Work with datasets and platforms including Worldscope, IBES, Lipper, Datastream and Refinitiv Workspace, developing a strong understanding of their structure, coverage and appropriate application
• Partner with Research Analysts, Engineering, Technology and Data Operations to translate analytical requirements into robust, scalable solutions
• Support index research, methodology development, rebalances and other operational activities where strong analytical and technical expertise is required
• Respond to internal and external analytical enquiries and contribute to client-facing analysis and materials
• Continuously improve existing code, processes and research infrastructure with a focus on scalability, automation, accuracy and maintainability

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 nextThe 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 skillsCandidates 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 assuranceExperience 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