Data Scientist – Equity Research
The role focuses on integrating fundamental and alternative datasets into equity research reports, leveraging machine learning and generative AI to enhance analyst workflows. Candidates will build internal AI tooling, evaluate third‑party models, and collaborate with analysts to deliver actionable insights at scale.
Skills required
About this role
Overview
The Jefferies Equity Research Data Strategy Team is a global team embedded within the Equity Research department, responsible for shaping and executing the department's data and AI strategy. On the data side, the team helps incorporate fundamental and alternative datasets into Analyst research reports, combining analysts’ domain expertise with our team’s technical skills to produce thoughtful, defensible, and actionable analysis of real-world behavior at scale. On the AI side, our team is responsible for building internal generative AI tooling along with evaluating third-party AI models and tools to enhance our analysts’ work. We help integrate AI capabilities into analysts’ daily workflows and ensure that first- and third-party datasets are fully AI-accessible to them. Statistics, data engineering, data science, and AI are cornerstones of our work.
As a Data Scientist at Jefferies, your focus will be to support the Research Analysts and the Data Strategy Team’s broader platform. The candidate will use technical and financial skills to implement ideas and requests from the Research Analysts, while also building and maintaining relationships with internal and external stakeholders, working in collaboration with the rest of the Global Data Strategy Team.
Key Responsibilities
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Query, transform, analyze, and combine large datasets in support of solving problems and implementing research ideas across sectors and data categories, occasionally developing statistical models to predict outcomes
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Enhance our platform through the creation and maintenance of tools, AI agents, MCP servers, and processes that streamline, scale, and standardize our ability to evaluate, clean, analyze, and disseminate data
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Contribute to the data centralization process, ensuring all first- and third-party data assets are AI-accessible and meet quality, lineage, and governance standards
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Present highly technical methods to non-technical stakeholders and translate open-ended questions into data-driven insights
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Maintain and build relationships with key internal and external stakeholders, including research teams, third-party data vendors, management, and possibly buy-side clients
Qualifications
Required
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Transferable experience on the sell-side or buy-side, in data science, data research, or similar function
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STEM degree with preference for Computer Science, Data Science, Engineering, Statistics, Quantitative Finance, and related disciplines
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Strong proficiency with Python, intermediate or better proficiency with SQL and/or Apache Spark
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Experience analyzing and visualizing large datasets
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Experience with AI-assisted development (Claude Code, GitHub CoPilot, Cursor, etc.)
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Familiarity with LLMs, LangChain, vector databases, and RAG pipelines
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Excellent communication skills with the ability to translate complex technical concepts for non-technical stakeholders
Preferred
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Demonstrated interest in fundamental equity research and financial modelling
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Experience with Databricks or Snowflake and cloud platforms such as AWS
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Experience with Atlassian project management tools (JIRA, Confluence, Bitbucket)
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Experience with knowledge graphs
Primary Location Full Time Salary Range of $100,000 - $120,000.
