Lead Learning Scientist

Faculty
London

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

Our education team, part of Faculty’s Public Services Business Unit, works with the organisations that shape education — from governments and school groups, to publishers, education companies, and assessment organisations — to design, build and assure AI systems in high-stakes settings where safety, accuracy and efficacy genuinely matter.

Recent work includes national education infrastructure, AI tutoring, assessment and content-quality systems, and the safety and evaluation of AI used by children. The market we serve is shifting from “can AI do it?” to “can you prove impact?”. Our clients increasingly want help building AI solutions that are engineered to improve learning outcomes, teacher time, and quality, and that are safe by design - and that is precisely why this role exists.

About the role

As Lead Learning Scientist, you will ensure that our clients’ AI-powered education solutions are grounded in learning science, measurably effective, and set a global standard for what trustworthy AI in education looks like. You will define and lead the learning science discipline at Faculty: setting the strategy for learning design and evaluation, creating and owning our Learning Science Playbook, and ensuring the systems we build genuinely improve how people learn.

Working closely with senior leadership and multidisciplinary delivery teams, you will shape the design of scalable, data-rich learning systems in close partnership with product, engineering and data science, and guide colleagues to embed best-in-class learning science into everything we design and build for clients.

This is a founding leadership mandate, and the variety and stakes are unusual: in a single year you might shape national curriculum-grounded infrastructure, the evaluation architecture for a high-stakes assessment product, and the safety case for an AI system used by children — in an organisation that treats evidence, evaluation and safety as the product, not a compliance afterthought.

What you’ll be doing

  • Leading the design of learning goals, skill models, adaptivity logic and feedback systems across flagship client engagements — from national education infrastructure to tutoring, assessment and content-quality systems.

  • Creating and owning Faculty’s Learning Science Playbook — defining best practice for scaffolding, feedback loops, measurement rubrics and data instrumentation (how we track learning progress through user interactions), applied across every build.

  • Designing and overseeing rigorous evaluations — formative, summative and quasi-experimental — that give clients credible evidence their systems improve learning, not just plausible outputs.

  • Partnering with product, data science and engineering leads within delivery squads to ensure learning systems are technically robust and pedagogically sound — translating learning science into requirements engineers can build and test against.

  • Contributing learning science expertise to Faculty’s safety and assurance work, helping evidence that AI systems used in education are safe, effective and fit for purpose.

  • Coaching and mentoring colleagues across product, UX and data science to apply learning science principles in day-to-day design and delivery decisions.

  • Acting as the internal and external subject-matter expert on learning science, representing Faculty in strategic conversations with senior client stakeholders.

Who we’re looking for

ESSENTIAL

  • Expert-level knowledge of the learning sciences, instructional design, and cognitive or behavioural science.

  • The ability to translate learning science into clear, specific requirements that technical teams can build against — you make pedagogy build-able.

  • Strong working practice in evaluating and measuring learning impact (for example mastery, retention and transfer), including designing studies and deciding what data to capture.

  • Experience working with technical teams — engineers, data scientists or product developers — to shape what gets built. You need not have written the code yourself, but you have influenced how real systems were designed and can hold credibility with the people who build them.

  • Technical literacy in how AI systems are built, with a genuine appetite to deepen that knowledge quickly.

  • Excellent communication skills: able to influence senior stakeholders — internally and client-side — and to represent the discipline externally.

DESIRABLE (NOT REQUIRED)

  • Hands-on experience building AI-driven or adaptive learning systems.

  • Familiarity with LLM architectures, retrieval-augmented generation, evaluation harnesses or learning analytics pipelines.

  • Experience across multiple client or product contexts — for example consulting, agency or platform settings serving many institutions.

Our Interview Process

  • Talent Team Screen (30 minutes)

  • Project Deep Dive with the Head of Education (60 minutes) — you will walk us through one project you have led from conception to delivery

  • Case Study and Technical Interview (60 minutes) — we will send you the brief 72 hours ahead

  • Cultural and Leadership 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.

Posted 2026-07-27

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