Hiring nowEducation, assessment and learning AI

AI Learning Scientist

Also called Educational AI Scientist

An AI Learning Scientist tests whether AI teaching and assessment tools help people learn, and for whom. They give a company evidence that its product works, and an honest account of where it does not.

What they do

They design and run studies on AI tutors, feedback tools and assessment features. That means framing a testable question, choosing a sensible comparison, recruiting a fair sample of learners and agreeing what counts as learning. They work with product and engineering to build prototypes that can be tested. They analyse results, including who benefits and who drops out. They check whether assessments measure what they claim to. They write up findings and limits in plain language, and they advise on risks such as over-reliance, bias and unequal access.

What a strong hire delivers

In the first months a strong hire agrees what learning means for the product and how it will be measured. They run a first study on a live feature or prototype and report results to the team. They produce a validity and limitations report that product, sales and leadership can all read. They also leave behind a repeatable way to test future changes.

How you can tell they are good

Ask them to walk through a learning study they designed, from question to result. Listen for clear outcome measures, thought about comparison groups and honest discussion of what went wrong. Ask how they would know a gain was real learning and not task completion. Good candidates name limits without being prompted and can explain findings to non-specialists.

Why it is hard to fill

The title varies widely, so searching by it misses people. Few candidates combine learning science, experimental rigour and hands-on familiarity with AI products. Most come from one side only: academic education research, psychometrics or product teams. Strong people are often settled in universities or established education organisations, and need a clear sense that the company will act on evidence, not just publish it.

Where to find them

Look in education research groups, psychometrics and assessment teams, and learning science programmes. Education technology companies employ people who run efficacy studies. Teachers and curriculum designers who moved into research are another source. Some come from human-computer interaction labs studying tutoring systems. Assessment bodies and learning platform companies are also worth approaching.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for an AI Learning Scientist

  1. Tell us about a learning study you ran. What was the question, the design and the result?

    A strong answer states a clear question, a sensible comparison and defined outcomes, then gives the result plainly, including null or mixed findings. Worry if they only describe usage or satisfaction, or cannot say what they would change.

  2. How would you tell whether a student using an AI tutor has learned, rather than just finished the task?

    Good answers separate performance during support from later unaided performance, mention delayed tests and transfer tasks, and discuss answer copying. Worry if they rely on completion rates, time on task or learner opinion alone.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We build AI-supported teaching and assessment, and we want evidence that it helps people learn. We are looking for an AI Learning Scientist to design and run studies, test our prototypes with real learners and tell us honestly what works, for whom and where it falls short.

What you will do

  • Design and run experiments on AI tutoring, feedback and assessment features
  • Define learning outcomes and measures with product and engineering
  • Analyse results, including differences between groups of learners
  • Assess the validity and fairness of AI-supported assessments
  • Write learning study and validity and limitations reports for technical and non-technical readers
  • Advise on risks such as over-reliance, bias and unequal access
  • Help the team build repeatable ways to test future changes

What you will bring

  • Demonstrated experience designing and running learning studies or educational experiments
  • Clear grasp of pedagogy and assessment, shown in past work
  • Sound analysis skills and honest reporting of limits
  • Experience working with learners, teachers or education products
  • Ability to explain findings to product, engineering and leadership
  • Practical approach to AI risk in learning settings

Nice to have

  • Psychometrics or test validation experience
  • Human-computer interaction research background
  • Experience testing tutoring prototypes or learning platforms

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Pedagogy and assessmentAdvancedDesign learning activities and valid assessments
  • Human-computer interactionAdvancedDesign and study interactions between people and AI
  • Experimental designWorkingChoose comparisons that identify credible effects
  • AI risk managementWorkingIdentify, assess, treat and monitor AI risks

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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