Senior Data Scientist
Faculty is hiring a Senior Data Scientist for a remote role open to applicants in United Kingdom. Level rates it ; you can apply on Level.
AI in this role
Lead bespoke AI and machine learning projects for retail and consumer sector clients as a Senior Data Scientist.
Why Faculty?
We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.
We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.
Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.
AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen.
Faculty’s Retail & Consumer team builds AI that re-engineers how retail and consumer businesses make decisions, from personalised promotions and pricing to range, inventory and customer acquisition. We combine deep sector expertise with outstanding scientific and technical capability to solve hard problems and embed the solutions in our clients’ core business processes.
About the role
As a Senior Data Scientist, you will lead high-impact AI projects and shape the technical direction of bespoke solutions for some of the most recognisable names in retail and consumer.
You will define the data science approach for each engagement, design robust software architectures, mentor colleagues and ensure delivery rigour across projects. You will also build deep client relationships and strengthen our reputation as a leader in practical, measurable AI.
What you’ll be doing
Leading project teams that deliver bespoke algorithms and high-stakes AI solutions to clients across the retail and consumer sector
Translating complex business problems into the right data science solutions, and mapping the end-to-end approach so it meets client needs and is technically feasible
Designing the software architecture for data science solutions, working alongside engineering colleagues
Partnering with our commercial teams to build client relationships and shape project scope for technical success
Owning the technical side of the client relationship on projects and in business development, helping to secure successful outcomes
Estimating delivery timelines and leading your team to deliver to a demanding schedule
Supporting the professional growth of data scientists on your projects through mentorship, coaching and feedback
Upholding best practice throughout the project lifecycle, including embedding responsible AI thinking in how problems are framed, not only in how models are evaluated
Contributing to hiring at Faculty
What we’re looking for
You have senior experience in a professional data science position or a quantitative academic field
You have broad knowledge of state-of-the-art ML and AI, and can apply it, along with novel ideas, to build algorithms for complex data science problems
You hold yourself to rigorous validation standards, ensuring models perform reliably in real-world conditions and edge cases
You can scope projects by assessing technical feasibility and breaking complex workstreams into clear delivery milestones
You have mastery of Python and relevant frameworks, and can architect production-grade infrastructure for sophisticated models and agentic AI systems
You communicate clearly, translating sophisticated models and quantitative findings into actionable strategy for client stakeholders
You care about accountability, transparency and responsible AI, and nurture those habits in the people around you
You enjoy mentoring and developing other data scientists
What we can offer you
The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We welcome applications from all backgrounds and are committed to an inclusive recruitment process. [Insert standard Faculty EEO / reasonable adjustments line]
Faculty is the professional challenge of a lifetime.
Our Recruitment Ethos
We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.
A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.
How we rate this
Senior Data Scientist at Faculty rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where software architecture was part of your work. What did you do?
- Tell me about a project where client management was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Safety, Machine learning, Data Science, Software Architecture, and Client Management. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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