Software Engineer - (Machine Learning Experience a plus) - hybrid in London
Software Engineer - (Machine Learning Experience a plus) - hybrid

Software Engineer - (Machine Learning Experience a plus) - hybrid in London

London Full-Time 28800 - 48000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Build innovative systems and enhance GenAI workflows in a fast-paced environment.
  • Company: Join FactSet, a leading tech company in financial data solutions.
  • Benefits: Enjoy flexible work, competitive salary, health benefits, and career development opportunities.
  • Why this job: Make a real impact with cutting-edge technology in the financial sector.
  • Qualifications: Proficiency in Python or TypeScript and 4+ years of software engineering experience.
  • Other info: Be part of a diverse community focused on sustainability and collaboration.

The predicted salary is between 28800 - 48000 £ per year.

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 the DSAI team at FactSet, where our mission is to enrich data from across the company to enable it to be used in GenAI workflows. Core to the DSAI infrastructure is a knowledge graph that connects financial concepts to the data available at FactSet. Engineers on the team maintain and enhance a GenAI powered software stack that operates at the intersection of financial data, knowledge management, and data engineering.

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 the product. An ideal candidate for the role would be an individual that has experience or a strong interest in working with generative AI and related technologies. They will also have the confidence to meaningfully contribute to team meetings in order to help lead discussions and drive outcomes.

What You'll Do
  • Build new systems to ingest and enrich data into an ontology.
  • Monitor and enhance the accuracy, performance, and observability of our GenAI RAG stack.
  • Evaluate new large language models, tools, and AI engineering techniques.
  • Improve query planning, optimization, and evaluation infrastructure.
  • Partner and collaborate with product development leads to identify technical requirements for future product enhancements.
  • Collaborate with teams across the organization to understand their data.
What We're Looking ForRequired Skills
  • Proficiency in Python, TypeScript, or similar language and its environment.
  • 4+ years of software engineering experience required.
  • Proficiency with API design.
  • Strong technical writing and presentation skills.
  • Familiarity with relational databases and data modeling techniques.
  • Bachelor's degree in computer science, computer engineering, or similar technical field or equivalent practical experience.
Desired Skills
  • Experience with Cloud platforms such as AWS or Heroku.
  • Experience or knowledge of CI/CD concepts and GitHub.
  • An interest in the financial services domain.
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.
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.

At FactSet, we celebrate difference of thought, experience, and perspective. Qualified applicants will be considered for employment without regard to characteristics protected by law.

Software Engineer - (Machine Learning Experience a plus) - hybrid in London employer: FactSet Research Systems Inc.

FactSet 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 career development, employees are empowered to thrive both personally and professionally in the vibrant city of London. Join a globally recognised company that values diversity and encourages meaningful contributions to shape the future of financial data solutions.
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Contact Detail:

FactSet Research Systems Inc. Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Software Engineer - (Machine Learning Experience a plus) - hybrid in London

✨Tip Number 1

Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.

✨Tip Number 2

Prepare for those interviews! Research the company and its culture, especially how they use AI in their products. Tailor your answers to show how you can contribute to their mission.

✨Tip Number 3

Show off your skills! If you’ve got projects or contributions to open-source software, make sure to highlight them. A portfolio can speak volumes about your capabilities.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!

We think you need these skills to ace Software Engineer - (Machine Learning Experience a plus) - hybrid in London

Proficiency in Python
Proficiency in TypeScript
Software Engineering Experience
API Design
Technical Writing Skills
Presentation Skills
Familiarity with Relational Databases
Data Modeling Techniques
Cloud Platforms (AWS, Heroku)
CI/CD Concepts
GitHub
Interest in Financial Services Domain

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the Software Engineer role. Highlight your experience with Python, TypeScript, and any machine learning projects you've worked on. We want to see how your skills align with what we're looking for!

Show Off Your Projects: Include links to your GitHub or any relevant projects that showcase your coding skills and creativity. This gives us a chance to see your work in action and understand your approach to problem-solving.

Craft a Compelling Cover Letter: Your cover letter should tell us why you're excited about this role at FactSet. Share your passion for generative AI and how you can contribute to our DSAI team. Let your personality shine through!

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us 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, TypeScript, and API design. Brush up on your knowledge of relational databases and data modelling techniques, as these are crucial for the role. Being able to discuss your experience with these technologies confidently will impress the interviewers.

✨Show Your Curiosity

FactSet values curiosity, so don’t hesitate to ask insightful questions about their GenAI workflows and how they integrate financial data. This shows that you’re not just interested in the job, but also in how you can contribute to their mission.

✨Prepare for Technical Challenges

Expect to face some technical questions or challenges during the interview. Practice coding problems related to data ingestion and enrichment, as well as query optimisation. This will help you demonstrate your problem-solving skills and technical prowess.

✨Highlight Collaboration Skills

Since the role involves working closely with product development leads and other teams, be ready to share examples of how you’ve successfully collaborated in the past. Discussing your ability to lead discussions and drive outcomes will resonate well with the interviewers.

Software Engineer - (Machine Learning Experience a plus) - hybrid in London
FactSet Research Systems Inc.
Location: London
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  • Software Engineer - (Machine Learning Experience a plus) - hybrid in London

    London
    Full-Time
    28800 - 48000 £ / year (est.)
  • F

    FactSet Research Systems Inc.

    1001-5000
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