UK

United Kingdom · Learning and development · Lead (8-12 years)

Lead Learning Evaluation Strategist

Here is the whole job, in plain words. What it is, what you decide, how you're judged, how people get here and where they go next. Then the part no course gives you: twelve AI tutors who learn your work.

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  • Experience bandLead (8-12 years)
  • Direct reports3-5 reports
  • Reports toManager, Learning Analytics & Impact
  • UK framework levelUsually a manager, or the deepest specialist in a team

Also advertised as Principal Learning Evaluation Specialist · Learning Analytics Lead · Head of Learning Measurement

Built on 43,079 real UK job descriptions we analysed · grounded in qualifications employers recognise

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

NCC Education Level 5 Extended Diploma in Computing with Data Science NCC Education Limited · Level 5 · covers 1 of 5 standards
Level 6 Award in Data-led Decision Making Institute of Sales Professionals · Level 6 · covers 1 of 5 standards
Pearson BTEC Level 5 Higher National Diploma in Computing for England Pearson Education Ltd · Level 5 · covers 1 of 5 standards
Pearson BTEC Level 5 Higher National Diploma in Digital Technologies Pearson Education Ltd · Level 5 · covers 1 of 5 standards
Level 6 Certificate in Professional Sales Institute of Sales Professionals · Level 6 · covers 1 of 5 standards

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Introduction to Data Science and Big Data NCC Education Level 5 Extended Diploma in Computing with Data Science
Data-led Decision Making Level 6 Award in Data-led Decision Making
Apply the Concepts of Data Science to Computer Engineering NOCN Level 5 Diploma in Computer Engineering (Information Technology and Data Science)
Data Analytics Pearson BTEC Level 5 Higher National Diploma in Computing for England

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
AI Governance Fluency using AI responsibly
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Your Plan Illustration

Built for Lead Learning Evaluation Strategist

4 units that map to this job, from the qualifications that cover it.

  1. Introduction to Data Science and Big Data NCC Education Limited · covers 1 of 5 standards Level 5
  2. Data-led Decision Making Institute of Sales Professionals · covers 1 of 5 standards Level 6
  3. Apply the Concepts of Data Science to Computer Engineering NOCN · covers 1 of 5 standards Level 5
  4. Data Analytics Pearson Education Ltd · covers 1 of 5 standards Level 5
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Lead Learning Evaluation Strategist?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skill this role is being asked for

  • Data Governance & Ethics for Learning Data
Why each one is rising

The future skills this job leans on

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Lead Learning Evaluation Strategist plan as you set up, starting with a Future Fluency module on using AI in your job. No card.

Your first Future Fluency module is free. After that, your AI tutor is £70 a month.

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3What this role really is

A Lead Learning Evaluation Strategist designs how learning programmes are measured, setting the rules and the questions behind the data.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

LMS/LXP Data Extraction (Workday Learning, Cornerstone OnDemand, Degreed, EdCast) Advanced

You'll be writing custom reports, understanding the underlying database schemas, using APIs to pull data directly, and troubleshooting complex data discrepancies between the LMS and other systems. You're the expert on getting data out of these platforms.

Survey & Assessment Platforms (Qualtrics, Questionmark) Advanced

You'll be designing complex, multi-branching surveys, implementing advanced features like conjoint analysis, and consulting on the psychometric soundness of assessments. You're the go-to for all things survey design.

Data Analysis (Python (pandas, Matplotlib), R, Excel (Power Query, data modelling)) Advanced

You'll be using Python or R for advanced statistical analysis, automating data cleaning processes, and handling large, complex datasets. For quick, ad-hoc analysis, you'll be an Excel wizard, especially with Power Query and robust data models.

Data Visualization (Tableau, Power BI, SQL) Advanced

You'll be building complex, interactive dashboards from scratch in Tableau or Power BI. This often means writing SQL queries to pull data directly from data warehouses to create compelling visualisations that drive executive decisions.

HRIS / Business Data (Workday HCM, SAP SuccessFactors, Anaplan, Snowflake) Advanced

You'll be directly querying HRIS data (with appropriate permissions) to correlate learning data with performance ratings, promotion rates, and attrition. You'll also be partnering with HRIS and Finance to integrate learning data into enterprise platforms for holistic business impact models.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing in Where you are nowThe step above
Evaluation Methodology Selection Follows pre-defined methodology for routine tasks, escalates variations to L2/L3. Selects appropriate methodology for standard projects from approved options, consults L3/L4 on complex cases. Designs and adapts methodologies for complex programmes, makes recommendations for new approaches, consults L4 on strategic alignment.
Budget Allocation for Evaluation Tools/Projects No budget authority. Requests resources via supervisor. Can propose small budget requests (up to £5K) for specific project needs, requires L3/L4 approval. Recommends budget allocation up to £20K for specific workstreams, requires L4/L5 approval.
Team Hiring & Performance No hiring or performance management authority. Provides informal feedback to peers, may assist in interviewing L1 candidates. Mentors L1/L2, provides input on performance reviews, assists in interviewing L2 candidates.
Data Source Integration & Strategy Extracts data from existing, approved sources following instructions. Identifies potential new data sources for specific projects, seeks L3/L4 approval for access. Proposes and tests integration of new data sources for specific workstreams, consults L4 on broader impact.

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

Evaluation Framework Adoption Rate
The percentage of major learning programmes that are designed and evaluated using your established measurement framework.
Target · 90% of all strategic L&D programmes

If we launch 10 significant programmes this quarter, 9 of them should have a clear, pre-defined evaluation plan based on your framework, with metrics agreed upfront with the business unit.

ROI Reporting Accuracy
The variance between the projected Return on Investment (ROI) for a learning programme and the actual, measured ROI after implementation.
Target · <10% variance (ideally <5%)

If you projected a £250K ROI for a sales training programme, and the actual measured impact was £230K, that's an 8% variance – which is within target and shows your initial estimates are pretty solid.

Average Time-to-Insight
The average time it takes from a learning programme's completion to the delivery of a comprehensive impact report to relevant stakeholders.
Target · 4 weeks (28 calendar days)

A leadership programme finishes on 1st March. The full Level 4 impact report, including business results, needs to be presented by 29th March. This means you've got to be organised and proactive in getting the data.

Learning Data Integrity Score
A measure of the completeness, accuracy, and consistency of data from key learning and business systems (e.g., LMS, HRIS, CRM) used for evaluation.
Target · 95% data integrity across core evaluation datasets

You pull completion data from the LMS and cross-reference it with HRIS records. If 5% of records have missing employee IDs or inconsistent programme names, your integrity score for that dataset is 95%. You'll be working to fix those gaps.

Strategic Influence & Consultation
The extent to which you are proactively sought out by business leaders and L&D partners for advice on how to measure the impact of new initiatives, rather than just being asked to 'run the numbers' after the fact.
  • You're invited to early-stage programme design meetings, not just evaluation meetings. Your recommendations on KPIs are adopted by VPs. L&D Business Partners consult you on programme design to ensure measurability upfront. People genuinely listen to your advice.
Team Development & Mentorship
Your ability to build, guide, and develop your team of Learning Evaluation Specialists, helping them grow their skills and take on more complex work.
  • Your direct reports successfully lead their own evaluation projects. They give positive feedback on your coaching and support. Junior team members show measurable improvement in their analytical and communication skills. You're seen as someone who helps people get better at their jobs.
Credibility with Finance & Senior Leadership
The level of trust and confidence that the Finance team and other senior leaders place in your evaluation methodologies and reported ROI figures.
  • The Finance team uses your L&D impact data in their own quarterly business reviews without challenging the methodology. Senior leaders reference your evaluation findings in strategic discussions. They ask you for your opinion on investment decisions.
Innovation in Evaluation Methods
Your proactive exploration and successful implementation of new, more effective, or more efficient evaluation methodologies and tools.
  • You introduce a new causal inference technique that provides clearer insights. You pilot and successfully integrate a new data visualisation tool. You share best practices from outside the organisation that we then adopt.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy
Seeing Data Drive Real Business Decisions

You get a real kick out of seeing your analysis directly influence a budget reallocation or a change in programme design. It's not just academic; it's about tangible impact.

Your report shows a particular leadership programme isn't driving behaviour change. L&D leadership decides to re-design it based on your findings, and you feel a genuine sense of accomplishment.

Building a Robust Measurement Function

You enjoy the challenge of creating systems, setting standards, and improving processes. You're not just doing the work; you're building the capability for others to do it better.

You successfully implement a new, standardised evaluation template that significantly reduces manual effort and improves data consistency across the team.

Mentoring and Developing Others

You find satisfaction in guiding junior analysts, helping them solve problems, and seeing them grow their skills. Their success is your success.

A specialist on your team successfully delivers their first Level 4 impact report to a business unit, and you know your guidance helped them get there.

What frustrates people
  • The Impossible ROI Request: Being asked to 'prove the ROI' of a mandatory compliance or soft-skills programme with no pre-agreed business metrics. It can feel like you're being asked to pull numbers out of thin air, turning your job into an exercise in creative accounting.
  • Vanity Metric Obsession: Dealing with stakeholders who absolutely refuse to look past 'butts in seats,' completion percentages, and high 'smile sheet' scores, even when your deeper analysis shows the programme had zero behavioural impact. It's like they only want to hear good news, not the truth.
  • LMS Data Wrangling: Honestly, you'll spend a good 40% of your time just exporting messy, inconsistent data from a clunky LMS, then manually cleaning and reformatting it in Excel before any real analysis can even begin. It's tedious, frustrating, and not what you signed up for.
  • The 'Level 4' Black Hole: Business leaders might enthusiastically support a programme, but when you follow up three months later for the crucial business impact data (like sales figures or efficiency metrics), they're suddenly 'too busy' to provide it. Your hard work hits a wall.
  • Political Pressure Cooker: You might feel implicitly (or even explicitly) pressured to find a positive story in the data for a senior executive's pet project, even when the results are mediocre or negative. Navigating this can be really tough.
  • The Manager Compliance Wall: Your entire Level 3 measurement strategy often depends on managers completing observation checklists for their team members, but you get a measly 15% response rate because 'they don't have time.' It undermines all your careful planning.
What this role does not give you
  • A perfectly clean, consistent data environment from day one. You'll be building that.
  • A purely academic, hands-off approach to analysis. You'll be deep in the business context.
  • A quiet, solitary role. You'll be influencing, collaborating, and often challenging.
  • Instant gratification on every project. Some impact takes months, even years, to fully materialise.

8Who you work with

This role is a big deal. You're the one who makes sure our learning investment isn't just a 'nice to have' but a quantifiable driver of business success. You'll directly influence where we spend our L&D budget, helping us cut programmes that don't work and double down on those that do. Your work provides the evidence needed to justify L&D's strategic importance at the highest levels of the organisation.

Inside the business
  • Manager, Learning Analytics & Impact (your direct boss)
  • L&D Business Partners (your main internal clients)
  • Business Unit VPs and Department Heads (the people whose teams you're impacting)
  • HRIS Team (for all the employee data you'll need)
  • Finance Team (they'll scrutinise your ROI numbers, so you'll need to get them on side)
Outside the business
  • Learning Technology Vendors (for data extraction and integration)
  • External Consultants (for specialist evaluation projects, occasionally)

9What you need before you start

Not a wish list. The things you would be expected to already have.

  • Proven experience (8+ years) in a dedicated learning evaluation, HR analytics, or business intelligence role, with a clear focus on demonstrating business impact.
  • A track record of designing and implementing comprehensive evaluation frameworks (e.g., Kirkpatrick, Phillips ROI) for complex learning programmes.
  • Advanced proficiency in statistical analysis and data visualisation tools (e.g., Python/R, Tableau/Power BI) for handling large, disparate datasets.
  • Demonstrable experience in leading projects or mentoring junior analysts, with a focus on developing their technical and analytical capabilities.
  • Exceptional communication skills, particularly in translating complex analytical findings into clear, actionable insights for non-technical senior stakeholders.
  • A strong understanding of data governance, privacy regulations (like GDPR), and ethical data handling practices.

10What to practise next

Where the job is going, and what to do about it starting this week.

Predictive Learning Analytics

The goal is to move beyond just reporting 'what happened' to predicting 'what will happen.' Imagine using data to anticipate future skill gaps, predict which employees are at risk of attrition due to lack of development, or forecast the success of a training programme before it even starts. This is where the real strategic value lies.

Time Series Analysis · Machine Learning Models (Regression, Classification) · Feature Engineering · Model Validation & Interpretation

  • Within 3 months: Take an introductory online course on machine learning for business or HR analytics (e.g., on Coursera, edX).
  • Within 6 months: Start experimenting with applying basic predictive models (e.g., linear regression) to historical learning and performance data.
  • Within 9 months: Develop a proof-of-concept predictive model for a specific L&D challenge (e.g., predicting programme completion rates or skill mastery).
  • Within 12 months: Present your predictive model's findings and potential business applications to L&D leadership.

Quick win: Use existing historical data to build a simple regression model that predicts a basic outcome (e.g., quiz scores based on time spent in a module). It's a low-stakes way to get started with predictive thinking.

11Staying current once you are in

What people here do to keep up
  • Regularly attend industry conferences and webinars focused on learning analytics, HR tech, and data science to stay current with trends and best practices.
  • Actively participate in online communities or forums dedicated to learning evaluation or people analytics to share knowledge and learn from peers.
  • Dedicate time to self-study in advanced statistical methods, machine learning, or new data visualisation techniques relevant to the field.
  • Seek out opportunities to present your work externally, perhaps at industry events or through published articles, to build your personal brand and our organisation's reputation.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

Data Governance & Ethics for Learning Data

With increasing data privacy regulations (like GDPR) and growing concerns about ethical AI use and employee monitoring, defining clear rules for how we collect, use, and store learning data is becoming critical. Get this wrong, and you've got a compliance nightmare on your hands.

  • Privacy by Design
  • Data Anonymisation & Pseudonymisation
  • Consent Management
  • Ethical AI Use in HR/L&D

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • Kirkpatrick Model of Evaluation
  • Phillips ROI Methodology
  • Brinkerhoff's Success Case Method (SCM)
  • Learning Transfer Analysis
  • Advanced Survey Design & Psychometrics
  • Causal Inference Methods

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    Senior Learning Evaluation Specialist (L3)

    3-5 years as an L3

    Skills to master

    • Deep expertise in a specific evaluation methodology (e.g., Phillips ROI), leading complex programme evaluations, mentoring junior colleagues, and demonstrating strong stakeholder management.

    You're ready to move on when

    • Successfully led 5+ end-to-end evaluations for strategic programmes, including Level 4 impact reporting.
    • Consistently received positive feedback on mentorship and coaching of L1/L2 specialists.
    • Proactively identified and implemented improvements to existing evaluation processes or tools.
    • Demonstrated ability to influence L&D partners on programme design for measurability.
  2. 2

    Data Analyst / Scientist from another domain (e.g., Marketing, Finance)

    5-8 years in data analysis, plus 1-2 years focused on L&D/HR context

    Skills to master

    • Translating core data science skills to the unique challenges of learning data, understanding L&D methodologies (Kirkpatrick, Phillips), and developing strong HR/business acumen.

    You're ready to move on when

    • Successfully completed projects linking learning data to business outcomes in a previous role.
    • Demonstrated a strong understanding of L&D principles and challenges (e.g., through self-study, certifications, or project work).
    • Proven ability to build and communicate data models to non-technical audiences.
    • Experience managing data integrity and complex datasets from various sources.
  3. 3

    HR Business Partner with strong analytical skills

    6-10 years as an HRBP, plus 2-3 years focused on analytics

    Skills to master

    • Deepening statistical analysis capabilities, mastering evaluation methodologies, and transitioning from advising on people issues to leading data-driven measurement strategies.

    You're ready to move on when

    • Successfully led data-driven HR projects (e.g., attrition analysis, talent segmentation) with measurable impact.
    • Developed strong proficiency in data analysis and visualisation tools (e.g., Excel advanced, Power BI).
    • Demonstrated a passion for and understanding of learning evaluation principles.
    • Proven ability to influence senior business leaders with data-backed recommendations.

15Where this role leads

The long view: This work can lead to directing learning effectiveness strategy, or moving into wider talent and organisational effectiveness roles.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Lead Learning Evaluation Strategist is actually changing.

Where it leads

Roles this leads to

Also named as a next step, with no page in the catalogue yet:

  • Principal Learning Scientist (Individual Contributor Path)

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Introduction to Data Science and Big Data, worked against Lead Learning Evaluation Strategist.

Introduction to Data Science and Big Data Level 5

Applied to your work in Lead Learning Evaluation Strategist

The objective of this unit is to provide learners with a systematic understanding of Data Science and Big Data concepts, including their characteristics and applications. Learners will develop proficiency in data collection, design, and modelling techniques, and will be able to select appropriate tools for data pre-processing and apply analytical techniques to generate insights from data.

How the thinking builds
  1. 1 Remember
  2. 2 Understand
  3. 3 Apply
  4. 4 Analyse
  5. 5 Evaluate
  6. 6 Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

Start my Lead Learning Evaluation Strategist plan, free
See Your Progress Grow Illustration
Lead Learning Evaluation Strategist
  • Kirkpatrick Model of Evaluation
  • Phillips ROI Methodology
  • Brinkerhoff's Success Case Method (SCM)
  • Learning Transfer Analysis
  • Advanced Survey Design & Psychometrics
  • Causal Inference Methods
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Lead Learning Evaluation Strategist is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. Manager, Learning Analytics & Impact (L5)

    3-5 years in the Lead role

    This is a step up into formal people management, where you'll be accountable for the entire Learning Analytics function, not just leading projects.

    • Vendor Management Leading selection and management of key learning tech and evaluation vendors.
    • Portfolio Management Overseeing the entire portfolio of evaluation projects and priorities.
    • Cross-Functional Integration Ensuring learning data integrates seamlessly with broader talent and business intelligence platforms.

  2. Principal Learning Scientist (Individual Contributor Path)

    3-5 years in the Lead role

    This is a deep dive into advanced technical expertise, becoming a recognised authority without formal people management.

    • Machine Learning Engineering for L&D Building and deploying advanced predictive models.
    • Learning Experience Design (Data-Driven) Informing highly personalised learning paths through analytics.
    • Experimental Design Architecting rigorous A/B tests and quasi-experiments for learning interventions.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be honest, a big chunk of evaluation work is about wrestling with data, cleaning it up, and trying to make sense of endless comments. What if you could spend less time on the grunt work and more time on the strategic thinking and compelling storytelling? That's where AI comes in.

We're not talking about replacing your brain; we're talking about giving you a seriously powerful co-pilot. AI tools can automate the repetitive, time-consuming parts of your job, freeing you up to focus on the 'human' elements: asking the right questions, interpreting nuanced results, and influencing decisions. Think of it as having a tireless assistant who loves cleaning data and summarising research.

Automated Data Janitor

Use AI-powered scripts (think Python with clever libraries) or smart tools to automatically pull data from your LMS or HRIS APIs, spot inconsistencies, merge different datasets, and flag any weird anomalies. It's like having a super-efficient cleaner for your data.

Insight Amplifier

Got thousands of open-ended survey comments? Instead of manually coding them for days, feed them into an AI model for instant sentiment analysis and topic modelling. You'll identify key themes, pain points, and 'aha!' moments in minutes, not weeks. Seriously powerful stuff.

Instant Lit Review

Need to quickly get up to speed on the latest academic studies or industry whitepapers about, say, 'measuring the impact of leadership coaching'? Use an AI research assistant to summarise the key findings, giving you a solid theoretical foundation for your measurement strategy in a fraction of the time.

Executive Summary Drafter

Once you've done all your brilliant analysis, feed the key data points, charts, and conclusions into a generative AI. It'll produce a well-structured first draft of your executive summary or PowerPoint narrative, saving you hours of staring at a blank page. You'll still refine it, of course, but the heavy lifting is done.

Common questions

Common questions

How do you become a Lead Learning Evaluation Strategist?

Common routes in include Senior Learning Evaluation Specialist (3-5 years as an L3), Data Analyst / Scientist from another domain (e.g., Marketing, Finance) (5-8 years in data analysis, plus 1-2 years focused on L&D/HR context) and HR Business Partner with strong analytical skills (6-10 years as an HRBP, plus 2-3 years focused on analytics). Times vary with prior experience.

Where can a Lead Learning Evaluation Strategist progress to?

This role can lead on to Manager, Learning Analytics & Impact (3-5 years in the Lead role) and Principal Learning Scientist (Individual Contributor Path) (3-5 years in the Lead role), depending on the skills you build.

What new skills matter most for a Lead Learning Evaluation Strategist?

Increasingly, Data Governance & Ethics for Learning Data. These are the skills our record of this role lists as growing.

Free tools

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Three free tools, no account needed. Each one ends with a role, a level and a way in.

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17Where to go from here

Other roles at Level 5

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

 More jobs in learning and development

Stay in the field you know and move sideways rather than up.
If you leave this industry

The analytics, strategic thinking and stakeholder skills involved apply beyond this field. They can lead to HR analytics leadership, business intelligence, or management consulting in other sectors.

This role profile is © 2026 Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Start my Lead Learning Evaluation Strategist plan, free What happens next: a free account, then we build your plan as you set up. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.