Senior Analyst, Quant Research

Overview

In this Senior Analyst role, you will develop and maintain Python and SQL-based research tools and data pipelines to support index research and analytics. You will work across quant research, data operations and engineering to translate requirements into scalable solutions, tackling data quality, validation and automation. You will apply quantitative techniques to portfolio analytics, risk and factor research while collaborating with cross-functional teams. This role offers hands-on coding, data exploration and problem-solving at scale, with a clear impact on investment analytics and index design.

Pay / Benefits

• healthcare
• retirement planning
• paid volunteering days
• wellbeing initiatives

Responsibilities

• Develop, test and maintain Python and SQL-based research tools, analytics and data pipelines with CI/CD
• Perform data validation and QA across large financial datasets, identifying root causes across data, code and methodology
• Create automation and AI-enabled tools to streamline research and operational workflows
• Support quantitative investment and index research, including factor analysis, regression, portfolio optimisation, risk modelling and performance analytics
• Work with Worldscope, IBES, Lipper, Datastream and Refinitiv Workspace to understand their structures and appropriate applications
• Partner with Research Analysts, Engineering, Technology and Data Operations to translate analytical needs into scalable solutions
• Support index research, methodology development, rebalances and other operational activities requiring analytical and technical input
• Contribute to client-facing analysis and materials and continuously improve code, processes and research infrastructure

Key requirements

• approximately 5 years of experience in quantitative development, financial data analytics or related field
• strong hands-on Python and SQL skills
• experience with pandas, NumPy, Git, testing, CI/CD
• cloud computing and modern development environments (VS Code, GitHub Copilot)
• practical experience developing with generative AI and AI agents
• good understanding of equity markets and quantitative techniques (regression, optimisation, factor investing, risk modelling)
• meticulous, detail-oriented, able to manage multiple priorities in a dynamic environment

• agile
• curious
• highly motivated problem solver
• Python
• SQL
• pandas

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