Level

Faculty

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 Faculty.

Level's read on this job

  • Little AI ●○○○ is how Level rates this data scientist role: aI is not part of the work.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include PyTorch, NLP and AI safety.
  • Level lists 78 other open roles at Faculty.
  • The role was posted in the last few days.

AI in this role

pytorch
nlpai-safety

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.

About the Team

Bringing medicine to patients is complex, expensive and high-risk. Faculty’s Life Science’s team is concentrated on building AI solutions which optimise the research and commercialisation of life-changing therapies.

We partner with major pharma firms, academic research centres and MedTech start-ups to design and deliver solutions which address critical healthcare challenges, and help to democratise health for all.

About the role

As a Senior Data Scientist, you will lead high-impact AI projects and shape the technical direction of bespoke solutions. This role requires hands-on technical excellence combined with crucial team leadership.


You will define data science approaches, design robust software architectures, mentor junior colleagues, and ensure delivery rigor across projects all while building deep client relationships and solidifying 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 sector.

  • Conceiving the core data science approach and designing the associated robust software architecture for new engagements.

  • Mentoring a small number of data scientists and supporting the professional growth of technical team members on projects.

  • Partnering with commercial teams to build client relationships and shape project scope for technical feasibility.

  • Contributing to Faculty’s thought leadership and reputation through delivering courses, public speaking, or open-source projects.

  • Ensuring best practices are followed throughout the project lifecycle to guarantee high-quality, impactful delivery.

Who we're looking for:

  • You possess senior experience in a professional data science position or a quantitative academic field.

  • You demonstrate strong programming skills, with the ability to be a fluent Python programmer, using core libraries (NumPy, Pandas) and a deep-learning framework (e.g., PyTorch).

  • You have a deep expertise in core data science paradigms (supervised/unsupervised, NLP, validation), demonstrating a proficiency across the standard data science toolkit, including the ability to develop new, innovative algorithms.

  • You bring a leadership mindset, focused on growing the technical capabilities of the team and nurturing a collaborative culture.

  • You exhibit commercial awareness, with experience in client-facing work and the ability to translate business problems into a rigorous mathematical framework.

  • You are skilled in project planning, assessing technical feasibility, estimating delivery timelines, and leading a team to deliver high-quality work on a strict schedule.

Our Interview Process

  1. Talent Team Screen (30 minutes)

  2. Take Home Technical Assessment

  3. Technical Interview (90 minutes)

  4. Commercial Interview (60 minutes)

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 11 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

NLPAI SafetyPyTorch

Also common in data scientist jobs at this level

Pay

Typical data scientist job
$166k

This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs

Questions you could be asked

  1. What NLP problem have you worked on, and how did you measure whether it actually worked?
  2. How do you think about the risk of an AI system in this kind of role failing silently?
  3. What are the limits of PyTorch that you've run into, and how did you work around them?

Adapt your resume

  • List these exact terms on your resume: NLP, AI Safety, and PyTorch. 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.

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