Role overview
- Work with large, messy, real-world enterprise datasets
- Apply LLMs and AI tooling to operational and analytical problems at scale
- Build data workflows and experiments using Python and Jupyter notebooks
- Run and analyse large-scale queries and model outputs
- Prototype and iterate quickly on AI-driven approaches
- Work closely with product, engineering, and founders on exploratory projects
- Translate ambiguous problems into structured investigations and solutions
- Help shape how AI is applied across procurement and supply chain workflows
- Have 3+ years of hands-on experience in data science, applied AI, analytics, or similar work
- OR a strong academic background (e.g. Master’s in Data Science, Machine Learning, Statistics, Mathematics, Computer Science, Physics, etc.) combined with 1–2 years of industry experience
- Strong Python skills
- Experience working in Jupyter notebooks
- Familiarity with LLMs, AI tooling, or applied machine learning workflows
- Strong analytical and problem-solving ability
- Comfort working independently on open-ended problems
- Ability to work pragmatically rather than over-engineering solutions
- Curiosity and enthusiasm for AI-native ways of working
- Experience applying LLMs to real-world datasets
- Experience with vector databases, embeddings, or retrieval systems
- Exposure to operational or enterprise data environments
- Background in highly analytical disciplines such as medicine, physics, maths, or engineering
Benefits
- Competitive Equity: play a real part in Magentic’s upside
- A salary of £60-70k
- Enhanced parental leave
- 25 days holiday exc bank holidays, plus an extra day for our Christmas shutdown
- In-office lunches provided
- Monthly organised socials and an additional flexible monthly social budget for team lunches, coffees, dinners, or activities with colleagues
- Salary sacrifice pension and nursery schemes
- Hybrid London HQ (WFH Thurs and every other Tues, with flex if you have appointments etc)
- Annual team retreat—a fully-funded off-site to recharge, bond, and build
- Initial call (30 mins): this first step is an opportunity for you to hear more about Magentic and the role, and for us to learn more about how your experience aligns with the role.
- Skills interview (60 mins with some prep): in this step, we'll ask you to present some of your work to us and discuss it.
- In-person interview: for the final step, we invite you to come meet the team in-person and work alongside us! We find this is the best way for candidates to get a sense of what working at Magentic is like. This day will include a culture interview, a role-specific task and a discussion of your work with the team.
About the company
At Magentic, we’re building AI systems that can autonomously run complex procurement and supply chain workflows for some of the world’s largest companies.
We’re tackling a genuinely hard real-world problem, helping global manufacturing supply chains become more resilient in an increasingly unpredictable world. It’s a massive space with huge untapped potential for AI.
We’re an early-stage company backed by Sequoia Capital, with a team bringing experience from OpenAI, Meta, Revolut, NASA and McKinsey & Company.
We’re looking for a Data Scientist to help us apply LLMs and AI tooling to large-scale, messy, real-world datasets, solving operational problems where the answers aren’t obvious and the impact is very tangible.
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Remote Ai Data Science Robotics Generative Ai