Senior Analyst, Quant Research

Role overview

Key responsibilities

• Develop, test, and maintain Python- and SQL-based research tools, investment analytics, and data pipelines using software engineering and CI/CD practices.
• Analyze and validate large financial datasets, investigate anomalies, and identify root causes across data, code, and methodology.
• Build 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 optimization, risk modeling, and performance analytics.
• Use Worldscope, IBES, Lipper, Datastream, and Refinitiv Workspace datasets and platforms.
• Partner across research, engineering, technology, and data operations to deliver robust, scalable analytical solutions.
• Support index research, methodology development, rebalances, and other operational activities.
• Respond to analytical enquiries and contribute to client-facing analysis and materials.
• Improve code, processes, and research infrastructure for scalability, automation, accuracy, and maintainability.

Candidate profile

• Approximately five years of experience in quantitative development, financial data analytics, quantitative research, or a related discipline.
• Strong hands-on Python and SQL skills.
• Good understanding of equity markets and quantitative techniques such as regression, optimization, factor investing, and risk modeling.
• Rigorous approach to financial data and quality assurance.
• Agile, curious, detail-oriented problem solver who learns quickly, takes ownership, and can manage changing priorities.

Desirable experience

• 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 desirable.

About LSEG and FTSE Russell