Role overview
FactSet ( NYSE:FDS | NASDAQ:FDS ) helps the financial community to see more, think bigger, and work better. Our digital platform and enterprise solutions deliver financial data, analytics, and open technology to more than 8,200 global clients, including over 200,000 individual users. Clients across the buy-side and sell-side, as well as wealth managers, private equity firms, and corporations, achieve more every day with our comprehensive and connected content, flexible next-generation workflow solutions, and client-centric specialized support. As a member of the S&P 500, we are committed to sustainable growth and have been recognized among the Best Places to Work in 2023 by Glassdoor as a Glassdoor Employees’ Choice Award winner. Learn more at www.factset.com and follow us on X and LinkedIn .
At FactSet, we celebrate difference of thought, experience, and perspective. Qualified applicants will be considered for employment without regard to characteristics protected by law.
What you'll work on
- Scale our unstructured financial document enrichment pipeline that powers FactSet’s knowledge graph to support the ingestion and enrichment of 500,000+ news, transcripts, and filings document chunks per day across dozens of financial domains.
- Enhance and scale our AWS-based infrastructure to ensure the efficient, reliable delivery of ML and AI projects, including the integration of agentic solutions.
- Work closely with other engineers and product developers to integrate and manage diverse domains of ML and NLP models. Offer expert advice on model selection and deployment strategies.
- In collaboration with agentic tooling (Claude Code, Cursor, CoPilot), manage the entire software development lifecycle, from the initial design and coding through to testing and the deployment of applications.
- Act as a mentor to team members, promoting a culture of innovation and continuous learning within the team.
Note : Although we utilize agentic tools extensively at FactSet (Claude Code, Cursor, GitHub Copilot), we expect candidates for this role to demonstrate strong software engineering and machine learning fundamentals during the interview process.
What we're looking for
- Experience with Knowledge Graphs and architecting LLM-powered solutions.
- Familiarity with financial data, applications, and specific industry challenges.
- Expertise in NLP libraries such as nltk and SpaCy and proficiency in unstructured text analysis.
- Demonstrable leadership capabilities and experience in mentoring or leading a team.
Interview process
The landscape of AI tools is rapidly evolving and FactSet engineers use AI tools extensively as a part of their daily work. During th
You are encouraged to use AI tools like ChatGPT, Claude, Copilot when:
- Refining your resume and cover letter for submission
- Preparing for your interview, and researching FactSet and its products
You may not use AI tools:
- During an interview, or
- When explicitly requested not to use AI tools