Location
London

Hours
Full Time

Salary
Negotiable

About the Role
FTSE Russell, part of London Stock Exchange Group, is a leading global index provider delivering benchmark, analytics and data solutions to asset owners, managers, investment banks, ETF providers and other financial institutions worldwide. This role is within the Equities & Multi-Asset Index Research & Design team, responsible for the development, design, research and enhancement of index methodologies, analytics and investment solutions. The team collaborates closely with Engineering, Technology, Data Operations, Product, Sales and clients to deliver innovative index capabilities and analytical solutions.

We are seeking a highly technical and versatile Senior Analyst in Quantitative Research & Development who thrives on solving problems across quantitative development, data analysis, research and operational delivery. This hands-on role requires agility to switch rapidly between priorities — from developing Python research tools or AI-enabled workflows to investigating complex data issues, validating investment analytics, or supporting research and client requests.

The successful candidate will take ownership of problems from investigation through resolution and work comfortably across multiple teams and disciplines, contributing to the continuous improvement of code, processes and research infrastructure with a focus on scalability, automation, accuracy and maintainability.

Experience
Approximately 5 years of experience in quantitative development, financial data analytics, quantitative research or a related discipline. Strong hands-on skills in Python and SQL are essential. Experience with pandas, NumPy, Git, testing, CI/CD, cloud computing and modern development environments such as VS Code and GitHub Copilot is highly desirable. Practical experience developing with generative AI and AI agents is a plus.

Good understanding of equity markets and quantitative techniques including regression, optimisation, factor investing and risk modelling. Proven ability to perform detailed data analysis, validation and quality assurance across large financial datasets.

About you
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 a dynamic environment. Strong collaboration skills to work effectively with Research Analysts, Engineering, Technology and Data Operations teams.

Ability to develop, test and maintain Python and SQL-based research tools, investment analytics and data pipelines applying strong software engineering and CI/CD practices. Comfortable supporting index research, methodology development, rebalances and other operational activities requiring strong analytical and technical expertise.

Qualifications
No specific formal qualifications are mandated, but a strong technical background in quantitative research, software development and financial data analytics is expected. A rigorous approach to financial data and quality assurance is essential.