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For Companies At a Glance
- Tasks: Design and develop AI models for real-world datasets and collaborate closely with a senior technical team.
- Company: FactTrace.ai, an innovative AI company focused on trust and clarity in data.
- Benefits: Competitive salary, equity participation, and opportunities for long-term growth.
- Why this job: Make a real impact by turning advanced models into reliable systems in a collaborative environment.
- Qualifications: PhD or equivalent experience in a quantitative field, strong Python skills, and a delivery mindset.
- Other info: Office-based role in Cambridge, ideal for those who thrive in hands-on, team-oriented settings.
The predicted salary is between 36000 - 60000 £ per year.
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 do not 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 to hr@facttrace.ai
AI Data Scientist: Applied Intelligence & Delivery in Cambridge employer: FactTrace
Contact Detail:
FactTrace Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Data Scientist: Applied Intelligence & Delivery in Cambridge
✨Tip Number 1
Network like a pro! Get out there and connect with people in the industry. Attend meetups, conferences, or even local events. You never know who might be looking for someone just like you!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those that involve real-world data. This will give potential employers a taste of what you can do and how you think.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to AI and data science. Think about how you can demonstrate your delivery mindset and ability to work with messy data.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of our team at FactTrace.ai.
We think you need these skills to ace AI Data Scientist: Applied Intelligence & Delivery in Cambridge
Some tips for your application 🫡
Craft a Compelling CV: Your CV is your first impression, so make it count! Highlight your relevant experience in AI and data science, especially any hands-on projects or roles that showcase your ability to work with real-world data.
Show Your Passion in the Note: In your short note, let us know what excites you about applied data science. Be genuine and specific about why you want to work with us at FactTrace.ai and how you see yourself contributing to our mission.
Demonstrate Your Technical Skills: Don’t forget to include your GitHub link! We love seeing your code and projects. It’s a great way for us to gauge your technical skills and see how you approach problem-solving in real-world scenarios.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at FactTrace
✨Know Your Stuff
Make sure you brush up on your Python and data science tools. Be ready to discuss your experience with machine learning concepts and how you've tackled messy, real-world data in the past. This role is all about practical application, so be prepared to share specific examples.
✨Show Your Delivery Mindset
FactTrace.ai is looking for candidates who can deliver clear outputs and timelines. During the interview, highlight projects where you’ve successfully moved from abstract ideas to concrete implementations. Talk about how you document assumptions and performance metrics.
✨Collaborate and Communicate
Since this role involves close collaboration with engineers and validation leads, demonstrate your teamwork skills. Share experiences where you’ve worked in a team setting, iterated based on feedback, and how you’ve contributed to technical reviews focused on learning and improvement.
✨Express Your Passion for Applied Data Science
In your short note and during the interview, convey what excites you about applied data science. Discuss why you want to work hands-on with real-world systems and how you see yourself contributing to the mission of bringing clarity and trust to complex data.
