Senior Analyst, Quant Research
LSEG is hiring a Senior Analyst, Quant Research in London, United Kingdom. Level rates it ; you can apply on Level.
Level's read on this job
- Uses AI ●●○○ is how Level rates this role: an ordinary role that requires AI tools.
- Tools and skills the posting cites include Copilot, Python and SQL.
- Level files it as a senior role.
- Level lists 657 other open roles at LSEG.
- The role was posted within the past week.
AI in this role
Senior quantitative analyst developing Python research tools and AI-enabled workflows for financial index research and data pipelines.
Role Profile
FTSE Russell is a leading global index provider, creating and managing benchmark, analytics and data solutions used by asset owners, asset managers, investment banks, ETF providers and other financial institutions worldwide. The role sits within the Equities & Multi-Asset Index Research & Design team, a global group responsible for the development, design, research and enhancement of index methodologies, analytics and investment solutions. The team works 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, 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.
Key Responsibilities
- 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.
Candidate Profile
The 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 skills. Experience 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. Candidates 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 assurance. 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 next.
Career Stage:
Senior AssociateLondon Stock Exchange Group (LSEG) Information:
Join us and be part of a team that values innovation, quality, and continuous improvement. If you're ready to take your career to the next level and make a significant impact, we'd love to hear from you.
LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth.
Our purpose is the foundation on which our culture is built. Our values of Integrity, Partnership, Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions.
Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.
We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone’s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
You will be part of a collaborative and creative culture where we encourage new ideas. We are committed to sustainability across our global business and we are proud to partner with our customers to help them meet their sustainability objectives. Our charity, the LSEG Foundation provides charitable grants to community groups that help people access economic opportunities and build a secure future with financial independence. Colleagues can get involved through fundraising and volunteering.
LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.
Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it’s used for, and how it’s obtained, your rights and how to contact us as a data subject.
If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.
How we rate this
Senior Analyst, Quant Research at LSEG rates 45 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.
Uses AI. An ordinary role that requires AI tools.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where quantitative research was part of your work. What did you do?
- Tell me about a project where data analysis was part of your work. What did you do?
- Tell me about a project where portfolio optimisation was part of your work. What did you do?
- Tell me about a project where factor analysis was part of your work. What did you do?
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- List these exact terms on your resume: AI agents, Quantitative Research, Data Analysis, Portfolio Optimisation, and Factor Analysis. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.
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