Data Scientist

About Magentic

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.

The Role

This is not a traditional analytics or engineering role.

We’re looking for someone who enjoys working deeply with data, experimentation, AI tooling, and problem solving, someone comfortable using Python, notebooks, LLMs, and structured thinking to solve non-trivial operational challenges.

You’ll work on applying AI models and data science approaches to complex enterprise datasets, helping uncover insights, automate workflows, and prototype intelligent systems quickly.

The ideal person is highly curious, pragmatic, and comfortable operating in ambiguity. You don’t need to be a production software engineer, but you do need to be technically capable, thoughtful, and able to independently execute meaningful work.

What You’ll Do:

• 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

You Might Be a Great Fit if You:

• 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

Bonus Points:

• 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

Compensation And Benefits

At Magentic, we recognise and reward the talent that drives our success. We offer:

• 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

Our Interview Process

There are a few components because it's really important that both we and you have all the information to make a great decision at this stage of our journey. We can move quickly through these stages, so let us know if you have any timelines we need to meet.

• 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.

Responsible AI Statement

At Magentic, we are committed to developing artificial intelligence that benefits humanity. We push the limits of AI's capabilities and are dedicated to its responsible and safe deployment. Recognising the profound impact of AI, we ensure that its development is centred around human needs and safety, incorporating a wide array of perspectives to fulfil our mission.

Equal Opportunities and Accommodations Statement

Magentic is committed to creating a diverse and inclusive workplace and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, gender, gender reassignment, marital or civil partnership status, age, disability, pregnancy or maternity, or any other basis as protected by the Equality Act 2010.

We actively encourage applications from candidates of all backgrounds and cultures and believe a diverse workforce enhances our ability to deliver innovative solutions. We also ensure that our employment decisions are based solely on individual qualifications, merit, and business needs.

Magentic is dedicated to providing reasonable accommodations to job applicants with disabilities. If you require any adjustments during the recruitment process, please indicate this in your application or contact us directly.