Financial Markets Data and Research Analyst

Overview

In this role you will conduct data-driven research on wholesale financial markets to support regulatory priorities. You will work with large regulatory datasets and collaborate with supervisors, policy specialists and market experts to illuminate market dynamics and risks. Your work informs policy and supervision decisions and contributes to meaningful regulatory outcomes. You will develop cross-market knowledge and build robust, evidence-based insights that shape regulatory thinking and industry practices.

Pay / Benefits

• 25 days annual leave plus bank holidays
• Flexible benefits scheme
• Non-contributory pension (8–12%) and life assurance
• Private healthcare with Bupa and income protection
• Volunteer time (35 hours annually)
• Office presence in London/Leeds/Edinburgh

Responsibilities

• Conduct research and analysis across wholesale financial markets to support regulatory priorities and decision-making
• Analyze large and potentially complex proprietary regulatory datasets, including transaction-level trading and derivatives data
• Collaborate with supervisors, financial market experts and policy specialists on analytical and research activities
• Contribute to medium-term research projects and time-sensitive analysis on current market issues
• Communicate findings effectively and build relationships with stakeholders across the FCA
• Develop knowledge across wholesale markets, financial products and relevant regulation while enhancing analytical and programming capabilities
• Take ownership of work, contribute research ideas and help shape project priorities and direction

Key requirements

• Prior experience developing skills in at least one analytical programming language for data analysis (Python, R, or SQL)
• Experience cleaning, transforming and analysing large and complex datasets
• Experience applying quantitative, economic, financial, or relevant theoretical knowledge to practical problems with an interest in financial markets or regulation

• Clear written communication
• Ability to work independently
• Collaborative mindset
• Python, R, or SQL programming for data analysis
• Analytical data manipulation of large datasets
• Quantitative research methods

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