AI Data Scientist: Applied Intelligence & Delivery

FactTrace
Cambridge
1 month ago
Applications closed

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About FactTrace.ai

FactTrace.ai builds AI systems that bring clarity, integrity, and evidence to complex data.


Our focus is not just intelligence, but trust— ensuring that AI outputs can be understood, validated, and relied upon in real‑world decision‑making.


After a period of incubation and research in 2025, FactTrace is now operating as a trading company and going public in January 2026. This next phase is about delivery, real‑world data, and outcomes under scrutiny.


The Role

We are looking for exceptional AI Data Scientists based in the UK who want to work side by side with engineers, validation leads, and the founder, turning advanced models into systems that run reliably in the real world.


This is a fully office-based role in Cambridge. We believe this phase of the company benefits from being in the same room: fast iteration, shared context, and deep collaboration.


This is not a pure research role.


You will be part of a small, senior technical team focused on shipping, validating, and improving models under real constraints.


What You’ll Do

  • Design and develop models for complex, real‑world datasets
  • Translate analytical ideas into deliverable, repeatable outputs
  • Work within an engineering pipeline to ensure models can run reliably
  • Collaborate closely with validation leads to test performance on real‑world data
  • Iterate based on feedback, results, and observed behaviour
  • Clearly document assumptions, limits, and performance
  • Participate in technical reviews focused on learning and improvement

What We’re Looking For

  • PhD, MPhil, or equivalent experience in Computer Science, Engineering, Mathematics, Physics, or a related quantitative field
  • Strong foundation in Python and data science tooling
  • Solid understanding of machine learning concepts and evaluation
  • Comfort working with messy, real‑world data
  • Ability to move from abstract reasoning to concrete implementation
  • A delivery mindset: clear outputs, clear assumptions, clear timelines

Candidates donot need to come from a specific university — we welcome applications from across the UK.


Nice to Have (Not Required)

  • Experience with deep learning, embeddings, or representation learning
  • Familiarity with PyTorch, TensorFlow, or similar frameworks
  • Interest in robustness, evaluation, or data integrity
  • Experience taking work from experimentation into production

Working Style & Location

  • Office-based in Cambridge
  • Close collaboration, fast feedback, shared ownership
  • Suited to people who enjoy building together, in person

Commitment & Growth

  • Full‑time role
  • Start date: asp
  • Competitive salary and early‑stage equity participation
  • Designed for long‑term growth within the core technical team

How to Apply

Please send:



  • Your CV
  • Your GitHub
  • A short note (a few paragraphs is enough) explaining:

    • What draws you to applied data science
    • Why you want to work hands‑on, in person, on real‑world systems



📩


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