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Data Scientist – Equity Research

Job in New York, New York County, New York, 10261, USA
Listing for: Jefferies
Full Time position
Listed on 2026-09-29
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst, Data Engineering
Salary/Wage Range or Industry Benchmark: 100000 - 120000 USD Yearly USD 100000.00 120000.00 YEAR
Job Description & How to Apply Below
Location: New York

JOB DESCRIPTION

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  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.

Overview

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
  • 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
  • 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
  • Contribute to the data centralization process, ensuring all first- and third-party data assets are AI-accessible and meet quality, lineage, and governance standards
  • Present highly technical methods to non-technical stakeholders and translate open-ended questions into data-driven insights
  • 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
  • Transferable experience on the sell-side or buy-side, in data science, data research, or similar function
  • STEM degree with preference for Computer Science, Data Science, Engineering, Statistics, Quantitative Finance, and related disciplines
  • Strong proficiency with Python, intermediate or better proficiency with SQL and/or Apache Spark
  • Experience analyzing and visualizing large datasets
  • Experience with AI-assisted development (Claude Code, Git Hub CoPilot, Cursor, etc.)
  • Familiarity with LLMs, Lang Chain, vector databases, and RAG pipelines
  • Excellent communication skills with the ability to translate complex technical concepts for non-technical stakeholders
Preferred
  • Demonstrated interest in fundamental equity research and financial modelling
  • Experience with Databricks or Snowflake and cloud platforms such as AWS
  • Experience with Atlassian project management tools (JIRA, Confluence, Bitbucket)
  • Experience with knowledge graphs

Primary Location Full Time Salary Range of $100,000 - $120,000.

About Us

Jefferies is a leading global, full-service investment banking and capital markets firm that provides advisory, sales and trading, research, and wealth and asset management services. With more than 40 offices around the world, we offer insights and expertise to investors, companies, and governments.

At Jefferies, we are committed to building a culture that provides opportunities for all employees regardless of our differences and supports a workforce that is reflective of the communities where we work and live. As a result, we are able to…

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