Data Scientist: AI & LLMs for Enterprise Ops

Data Scientist: AI & LLMs for Enterprise Ops

Full-Time 63000 - 77000 £ / year (est.) No working from home possible
Socket.dev

At a Glance

  • Tasks: Apply AI and LLMs to tackle complex enterprise data challenges.
  • Company: Magentic, a forward-thinking tech company based in London.
  • Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
  • Other info: Join a dynamic team focused on innovation and practical solutions.
  • Why this job: Make a real impact by solving operational problems with cutting-edge technology.
  • Qualifications: Experience in Python, data workflows, and a passion for AI.

The predicted salary is between 63000 - 77000 £ per year.

Magentic in London is seeking a Data Scientist to apply LLMs and AI tooling to large, messy enterprise datasets, solving operational problems where the answers aren’t obvious.

You’ll build data workflows in Python/Jupyter, run large-scale queries, prototype AI-driven approaches, and work with product, engineering, and founders on exploratory projects.

The role emphasizes curiosity, pragmatism, and the ability to operate in ambiguity, with a strong tilt toward practical impact.

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Data Scientist: AI & LLMs for Enterprise Ops employer: Socket.dev

Multiverse is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of Edinburgh. With a commitment to employee growth through comprehensive upskilling opportunities and a robust benefits package, including generous holiday allowances and health support, Multiverse empowers its team to thrive in the rapidly evolving AI landscape. Join us to be part of a mission-driven company that values diversity and inclusion while shaping the future of education and workforce development.

Socket.dev

Contact Details:

Socket.dev Recruitment Team

We think you need these skills to ace Data Scientist: AI & LLMs for Enterprise Ops

Python
SQL
Problem-Solving Skills
Communication Skills
Data Engineering
Automation
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