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Factset

Machine Learning Engineer - Python, SQL, NoSQL, and Vector databases

Reposted 23 Hours Ago
Be an Early Applicant
In-Office
London, Greater London, England
Mid level
In-Office
London, Greater London, England
Mid level
The role involves scaling financial document enrichment, enhancing AWS infrastructure, managing ML/NLP model integration, and mentoring team members at FactSet.
The summary above was generated by AI

FactSet creates flexible, open data and software solutions for over 200,000 investment professionals worldwide, providing instant access to financial data and analytics that investors use to make crucial decisions.  

At FactSet, our values are the foundation of everything we do. They express how we act and operate, serve as a compass in our decision-making, and play a big role in how we treat each other, our clients, and our communities. We believe that the best ideas can come from anyone, anywhere, at any time, and that curiosity is the key to anticipating our clients’ needs and exceeding their expectations.  

Your Team's Impact 

Join FactSet's Data Solutions AI team where our mission is to transform how financial professionals discover and interact with data through cutting-edge AI and machine learning technologies. We're building intelligent systems that enable clients to ask natural language questions about financial data and receive actionable insights powered by our semantic enrichment platform. At the core of our infrastructure is a knowledge graph that connects financial concepts to FactSet's comprehensive structured and unstructured data offerings, powering innovative solutions that push the boundaries of FactSet’s products. 

What You'll Do 

  • 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 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. 

  • Implement robust observability and tracing across data enrichment pipelines to ensure end-to-end transparency to product and engineering stakeholders, enabling proactive monitoring and alerting, and rapid identification of quality or performance issues. 

 

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 

You will be working on a team in a fast-paced environment where you will have the opportunity to influence the design and architecture of our products. An ideal candidate for the role would be an individual who has experience or a strong interest in working with data pipelines for unstructured data, a history of successfully deploying machine learning models to production, an interest in knowledge graphs and semantic web technologies, and a passion for experimentation. 

 

 

Required Skills 

  • 3-5 years of software engineering experience with significant focus on AI/ML solutions in production environments. 

  • Demonstrated expertise in cloud architecture, primarily AWS, with familiarity across a broad range of services. 

  • Strong understanding of Natural Language Processing, Machine Learning, and Deep Learning fundamentals with proven history of model development and deployment. 

  • Proficiency in Python, API development, and software engineering paradigms. 

  • Excellent communication abilities, capable of engaging both technical and business audiences and leading cross-functional projects. 

  • Knowledge of major database architectures including SQL, NoSQL, and Vector databases. 

 

 

 

Desired Skills 

  • Experience with knowledge graphs and architecting LLM-powered solutions. 

  • Experience with enhancing and scaling event-driven architectures. 

  • Familiarity with financial data, applications, and specific industry challenges. 

  • Expertise in NLP libraries such as NLTK, spaCy, or GLiNER and proficiency in unstructured text analysis. 

  • Demonstrable leadership capabilities and experience in mentoring or leading a team. 

 

What's In It For You 

At FactSet, our people are our greatest asset, and our culture is our biggest competitive advantage. Being a FactSetter means: 

  • The opportunity to join an S&P 500 company with over 45 years of sustainable growth powered by the entrepreneurial spirit of a start-up. 

  • Support for your total well-being. This includes health, life, and disability insurance, as well as retirement savings plans and a discounted employee stock purchase program, plus paid time off for holidays, family leave, and company-wide wellness days. 

  • Flexible work accommodations. We value work/life harmony and offer our employees a range of accommodations to help them achieve success both at work and in their personal lives. 

  • A global community dedicated to volunteerism and sustainability, where collaboration is always encouraged, and individuality drives solutions. 

  • Career progression planning with dedicated time each month for learning and development. 

  • Business Resource Groups open to all employees that serve as a catalyst for connection, growth, and belonging. Learn more about our benefits here. 

Salary is just one component of our compensation package and is based on several factors including but not limited to education, work experience, and certifications. 

 

 

Use of AI tools during the interview process 

As a team building AI-powered products in collaboration with agentic tools, we recognize that AI tools are becoming integral to modern software development. At the same time, our interview process is intended to assess your individual critical thinking, technical judgement, and problem-solving skills. 

 
You may use AI tools (e.g., 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 a live interview unless otherwise noted. This is an opportunity for us to assess your unique skill set and your ability to reason through practical problems. 

Company 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. 

Top Skills

AWS
Deep Learning
Machine Learning
Natural Language Processing
NoSQL
Python
SQL

Factset London, England Office

One Snowden Street, , London, United Kingdom, EC2A 2DQ,

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