At a Glance
- Tasks: Join our AI team to revolutionise financial data interaction with cutting-edge machine learning.
- Company: Fact Set, a leading S&P 500 company with a culture of innovation.
- Benefits: Enjoy flexible work, health benefits, and career progression opportunities.
- Other info: Collaborative environment with a commitment to sustainability and personal growth.
- Why this job: Make a real impact in finance by developing intelligent systems that empower users.
- Qualifications: 3-5 years in software engineering with a focus on AI/ML and strong Python skills.
The predicted salary is between 36000 - 60000 € per year.
Fact Set 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.
Your Team's Impact
Join Fact Set'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 Fact Set's comprehensive structured and unstructured data offerings, powering innovative solutions that push the boundaries of Fact Set’s products.
What You'll Do
- Scale our unstructured financial document enrichment pipeline that powers Fact Set’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, Co Pilot), 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.
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 that has experience or a strong interest in working with data pipelines for unstructured data, a history of success deploying machine learning models to production, an interest in knowledge graph 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 successful 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, No SQL, and Vector databases.
Desired Skills
- 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.
What's In It For You
At Fact Set, our people are our greatest asset, and our culture is our biggest competitive advantage. Being a Fact Setter 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.
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
The landscape of AI tools is rapidly evolving and Fact Set engineers use AI tools extensively as a part of their daily work. During the interview process, you are encouraged to use AI tools like Chat GPT, Claude, Copilot when:
- Refining your resume and cover letter for submission
- Preparing for your interview, and researching Fact Set and its products
You may not use AI tools:
- During an interview, or
- When explicitly requested not to use AI tools
Company Overview:
Fact Set (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. At Fact Set, we celebrate difference of thought, experience, and perspective. Qualified applicants will be considered for employment without regard to characteristics protected by law. At Fact Set, 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.
Machine learning engineer - python, sql, nosql, and vector databases in London employer: FactSet Research Systems Inc.
Fact Set is an exceptional employer that prioritises the well-being and growth of its employees, offering a dynamic work culture that fosters innovation and collaboration. With flexible work arrangements, comprehensive benefits including health and retirement plans, and a strong commitment to professional development, employees are empowered to thrive in their careers while contributing to meaningful projects in the financial sector. Joining Fact Set means being part of a globally recognised S&P 500 company that values diversity and encourages a spirit of entrepreneurship, making it an ideal place for those looking to make a significant impact.
Contact Detail:
FactSet Research Systems Inc. Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Machine learning engineer - python, sql, nosql, and vector databases in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Fact Set. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Prepare for your interview by diving deep into machine learning concepts and the specific tools mentioned in the job description. Show us you know your stuff and can talk about real-world applications!
✨Tip Number 3
Don’t just focus on your technical skills; highlight your soft skills too! Being able to communicate complex ideas clearly is key, especially when working with cross-functional teams.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining the team at Fact Set.
We think you need these skills to ace Machine learning engineer - python, sql, nosql, and vector databases in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with Python, SQL, and NoSQL databases, as well as any relevant projects that showcase your skills in AI and ML.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about working with financial data and how your background aligns with our mission at Fact Set. Be genuine and let your personality come through.
Showcase Your Projects:If you've worked on any interesting projects related to machine learning or natural language processing, make sure to mention them. We love seeing practical applications of your skills, so don’t hold back!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at FactSet Research Systems Inc.
✨Know Your Tech Stack
Make sure you’re well-versed in Python, SQL, NoSQL, and vector databases. Brush up on your knowledge of AWS services too, as they play a crucial role in the infrastructure at Fact Set. Being able to discuss your experience with these technologies confidently will show that you're ready to hit the ground running.
✨Showcase Your ML Experience
Prepare to discuss specific machine learning projects you've worked on, especially those involving unstructured data. Be ready to explain your model selection process and deployment strategies. This is your chance to demonstrate your expertise and how it aligns with the needs of the Data Solutions AI team.
✨Communicate Effectively
Since you'll be engaging with both technical and business audiences, practice explaining complex concepts in simple terms. Think about how you can convey your ideas clearly and concisely, as strong communication skills are essential for this role.
✨Emphasise Collaboration and Mentorship
Fact Set values teamwork and innovation, so be prepared to share examples of how you've collaborated with others or mentored team members in the past. Highlighting your leadership capabilities will show that you can contribute to a positive team culture.
