UK

United Kingdom · Learning and Development · Senior (5-8 years)

Senior Global Learning Analytics Manager

Here is the whole job, in plain words. What it is, a real day, 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.

  • Experience bandSenior (5-8 years)
  • Direct reportsNo direct reports
  • Reports toGlobal Learning Analytics Manager Manager
  • UK framework levelUsually a manager, or the deepest specialist in a team

Also advertised as Senior Learning Data Analyst · Learning & Development Insights Lead · People Analytics Specialist (L&D Focus)

Built on an analysis of 43,079 real UK job descriptions · grounded in qualifications employers recognise

Start with a free Future Fluency check, tuned to Senior Global Learning Analytics Manager

Ten quick questions, one per Future Fluency, asked against this role rather than a generic one. About five minutes, and no card.

Start the check, free

1What this role really is

This isn't just about pulling numbers; it's about making sense of them for our global learning programmes. You'll be the one digging deep into data from our learning systems, HR platforms, and surveys to figure out what's actually working, what isn't, and why. We need someone who can translate complex data into clear, actionable stories that help our leadership make smarter decisions about how we develop our people across the world. It’s a bit like being a detective, but your clues are data points and your reward is seeing better learning outcomes.

2What you'd actually use

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

Power BI / TableauAdvanced

Designing, building, and deploying complex, interactive dashboards from scratch. You'll use advanced DAX or LOD calculations and manage multiple data sources to create compelling visualisations for leadership.

LMS/LXP APIs (e.g., Cornerstone, Workday Learning, Degreed)Intermediate

Extracting data programmatically via REST APIs to get beyond standard UI reports. You'll understand the nuances of xAPI/cmi5 data structures and how to pull the right information.

HRIS Reporting (Workday Report Writer / SuccessFactors BIRT)Intermediate

Creating custom reports and calculated fields from our HRIS to get employee demographics, performance ratings, and job roles. You'll understand the core HCM data objects and how they relate to learning data.

SQL (PostgreSQL, T-SQL)Advanced

Writing complex multi-join queries, Common Table Expressions (CTEs), and window functions to transform raw data from various sources into a clean, usable format for analysis. This is your bread and butter for data manipulation.

Python (pandas, NumPy, scikit-learn)Advanced

Using scripts for advanced data cleaning, transformation, statistical analysis, and building predictive models. You'll be comfortable with these libraries for deeper analytical work.

Qualtrics / SurveyMonkeyIntermediate

Implementing complex survey logic, branching, and automated triggers for feedback collection. You'll also use these tools to analyse text data from open-ended feedback, not just quantitative scores.

Jira / ConfluenceIntermediate

Creating project plans, managing sprint backlogs for analytical projects, and writing technical documentation for data models and methodologies. You'll keep our work organised and transparent.

3What 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 inWhere you are nowThe step above
Project Methodology & Tool SelectionProposes options, but requires full approval from a senior analyst or manager.Chooses methodology for routine tasks; consults manager for complex or novel approaches. Selects standard tools.Full authority to define analytical methodology and select technical tools (e.g., Python libraries, specific Power BI features) within project scope. Informs manager of choices.
Data Interpretation & RecommendationsPresents findings and potential interpretations; recommendations are drafted with guidance and require full review.Independently interprets data for routine requests and drafts recommendations; manager reviews for strategic implications.Independently interprets complex data, forms actionable recommendations, and presents directly to L&D leadership or HRBPs. Manager is informed, not necessarily approving every detail.
Stakeholder Communication StrategyCommunicates with immediate team and supervisor; all external communication drafted with guidance.Communicates directly with internal clients on project updates and data requests; manager reviews key messages.Designs and executes communication strategy for analytical findings to senior internal stakeholders (e.g., VPs, Directors). Consults manager on highly sensitive or political communications.
Data Quality Issue ResolutionIdentifies data quality issues and reports them to a senior team member.Investigates root causes of data quality issues and proposes solutions; manager approves implementation.Leads investigation and resolution of complex data quality issues, working with IT or vendors. Recommends system improvements and implements approved fixes. Informs manager of progress and impact.
Budget for Small Tools/ResourcesNo budget authority; requests resources through supervisor.Can request small, pre-approved resources (e.g., a specific dataset purchase up to £500) with manager approval.Recommends and justifies expenditure for project-specific tools or data sources up to £10K; requires manager's final sign-off.

4How you'll be judged

The scoreboard, honestly: the hard targets, how often each one is actually looked at, and the quiet human signals that never make it onto a dashboard.

Project Completion & Impact
Successfully delivering complex analytical projects that address key L&D or business questions.
Target · 85% of assigned projects completed on time and delivering actionable insights.

Delivered a skills gap analysis that led to a £150,000 reallocation of L&D budget to critical emerging skills, completed within the agreed 10-week timeline.

Insight Adoption Rate
How often your analytical recommendations are actually taken up and acted upon by L&D leadership or business partners.
Target · 60% of key recommendations result in a measurable change in L&D strategy or programme design.

Your analysis showed that a particular compliance training wasn't reducing incidents. L&D then redesigned the programme based on your findings, leading to a 10% drop in reported incidents.

Mentee Development & Retention
The growth and engagement of any junior analysts you're informally mentoring.
Target · At least one mentee shows significant progress (e.g., takes on more complex tasks, improves code quality) within 12 months, and remains with the team.

Helped a junior analyst improve their SQL skills to the point where they could independently build a new data extract, and they expressed high job satisfaction.

Data Quality Improvement
Identifying and helping to resolve underlying data quality issues across our learning and HR systems.
Target · Reduce identified critical data errors by 20% across key L&D datasets annually.

Worked with IT to fix an issue where 5% of learning completion data was not syncing correctly from the LMS, ensuring more accurate reporting for all future analyses.

Stakeholder Trust & Influence
Being seen as a credible, go-to expert who can be relied upon for objective, well-communicated insights.
  • You're proactively invited to strategic L&D planning sessions. Leaders ask your opinion before making big programme decisions. Your presentations are clear, concise, and lead to productive discussions, not just more questions. People actually *listen* to your data stories.
Proactive Problem Solving
Identifying potential data issues or analytical needs before they become urgent problems, and proposing solutions.
  • You flag a potential data discrepancy in the LMS before anyone else notices. You suggest a new way to measure learning transfer for a programme that's about to launch. You don't just answer the question asked
  • you anticipate the next two questions.
Analytical Rigour & Innovation
Applying sound statistical methods and exploring new analytical approaches to solve complex L&D questions.
  • Your analyses consistently stand up to scrutiny. You're experimenting with new modelling techniques (e.g., predictive analytics for attrition). You're not just running the same reports
  • you're pushing the boundaries of what we can learn from our data.
Mentorship & Knowledge Sharing
Effectively guiding and developing junior team members, and sharing your expertise with the wider L&D team.
  • Junior analysts come to you for advice. You're running informal workshops on data best practices. You're contributing to our team's documentation and helping others understand complex methodologies. People feel comfortable asking you 'silly' questions.

5Would you like it

The honest version. What people enjoy, and what grinds them down.

What people enjoy
Solving Complex Puzzles

You'll be faced with ambiguous questions like 'Does our new onboarding programme actually reduce early attrition?' and you'll get to design the entire analytical approach to answer it. It's like a new riddle every week.

Spending a full day wrestling with disparate datasets to create a single, unified view of learner engagement, and finally seeing the pieces click into place.

Driving Tangible Impact

Your analyses won't just sit in a report; they'll directly influence how we spend our L&D budget, design new programmes, and ultimately help our employees develop. You'll see your work make a difference.

Presenting data that convinces leadership to invest in a new coaching programme for managers, and then seeing positive shifts in team performance metrics six months later.

Continuous Learning & Mastery

The world of data and learning science is always evolving. You'll be constantly learning new statistical techniques, exploring new data visualisation tools, and deepening your understanding of human behaviour and learning theory.

Spending a few hours each week experimenting with a new Python library for text analysis to see if it can improve how we categorise open-ended feedback.

What frustrates people
  • The 'Causality vs. Correlation' Battle: Constantly explaining to senior leaders that just because sales went up after a training programme doesn't mean the training *caused* it. You'll spend half your life trying to isolate variables, and they'll still ask for a single ROI number.
  • Garbage In, Garbage Out: Your analysis is only as good as the data. You will spend a significant chunk of your time cleaning, merging, and validating messy data from the LMS, HRIS, and a dozen other systems that were never designed to talk to each other.
  • The Quest for the 'One ROI Number': Leadership will relentlessly ask for a single, simple ROI figure for all L&D spending. You will relentlessly explain why this is a methodological nightmare and a misleading metric, but they'll still ask for it next quarter. Every quarter.
  • Data Silos & Gatekeepers: Begging the Finance department for performance data or the Sales Ops team for quota attainment data is a full-time job involving politics, horse-trading, and endless meetings. People guard their data like dragons.
  • 'Flavor of the Month' Metrics: A new CHRO arrives and suddenly everything needs to be measured in terms of 'Learning Velocity' or some other buzzword, forcing you to abandon your carefully constructed analytics roadmap and start from scratch.
  • LMS Reporting Sucks: The built-in reporting module of nearly every major LMS is inflexible and inadequate, forcing you to build complex, brittle workarounds just to get basic data out. It’s a constant battle.
What this role does not give you
  • A perfectly clean, ready-to-analyse dataset handed to you on a plate.
  • A quiet, predictable work environment where priorities never shift.
  • Immediate, universal adoption of every single insight you produce.
  • A role where you only build models and never have to explain them to non-technical people.

6Who you work with

This role directly shapes our global L&D strategy by providing evidence-based recommendations. You'll help us optimise our learning investment, identify critical skill gaps, and prove the tangible business value of our people development efforts. Essentially, you'll be giving us the data-driven confidence to make big decisions about our most valuable asset: our people.

Inside the business
  • Director of L&D
  • HR Business Partners (HRBPs)
  • Talent Acquisition Lead
  • IT Data Engineering Team
  • Product Team (for learning platforms)
  • Finance Business Partners
Outside the business
  • Learning content vendors
  • Learning platform providers (e.g., Cornerstone, Workday Learning)
  • External research partners

7What you need before you start

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

  • At least 5 years of hands-on experience in a data analytics role, with a significant portion focused on HR, People, or Learning analytics.
  • Proven ability to lead analytical projects from conception to delivery, including stakeholder management and presentation of findings.
  • Advanced proficiency in SQL for complex data manipulation and extraction (you should be able to write CTEs and window functions in your sleep).
  • Strong experience with at least one major BI tool (Power BI or Tableau) for building complex, interactive dashboards.
  • Demonstrable experience with Python (pandas, NumPy) for data cleaning, transformation, and statistical analysis.
  • A solid understanding of statistical methods (e.g., regression, hypothesis testing, A/B testing) and when to apply them.
  • Experience working with data from HRIS (e.g., Workday, SAP SuccessFactors) and/or LMS/LXP platforms (e.g., Cornerstone, Degreed).

8What to practise next

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

Enterprise BI Governance & Performance Optimisation

As our dashboards grow, performance issues and inconsistent reporting become a real headache. You'll need to understand how to keep our BI ecosystem healthy and reliable.

Data Model Optimisation (Star Schema) · DAX/LOD Optimisation · Row-Level Security (RLS) · Deployment Pipelines & Version Control · Monitoring & Alerting

  • This week: Review the performance of one of our existing complex dashboards and identify potential bottlenecks.
  • This month: Research best practices for Power BI Premium or Tableau Server governance and data model design.
  • Month 2: Take an advanced course on DAX or Tableau performance optimisation.
  • Month 3: Propose and implement a small-scale improvement to an existing dashboard's performance or security.
  • Ongoing: Actively participate in discussions with our IT Data Engineering team about BI infrastructure.

Quick win: Start using the Power BI Performance Analyser or Tableau's built-in performance recording to understand where your dashboards are spending their time. Small tweaks can make a big difference.

MLOps for Learning Models

Building a predictive model is one thing; deploying it, monitoring its performance, and retraining it automatically is another. As we move towards more advanced analytics, operationalising these models will be key.

Model Versioning & Experiment Tracking · Automated Retraining Pipelines · Model Monitoring & Alerting · Containerisation (Docker) · Cloud ML Platforms (Azure ML, AWS SageMaker)

  • This week: Read an introductory article on MLOps and its importance in data science.
  • This month: Explore Docker and containerise a simple Python script you've already written.
  • Month 2: Take an online course on MLOps or a cloud-specific ML platform (e.g., Azure ML Fundamentals).
  • Month 3: Work with IT Data Engineering to understand our current MLOps capabilities and identify a pilot project for a learning model.
  • Ongoing: Experiment with open-source MLOps tools like MLflow or Kubeflow in a sandbox environment.

Quick win: Start incorporating structured experiment tracking (even just in a spreadsheet) for your predictive models, noting parameters, data versions, and performance metrics. This builds good MLOps habits early.

9Staying current once you are in

What people here do to keep up
  • Regularly attending industry conferences or webinars on People Analytics, Learning Technologies, or Data Science (e.g., People Analytics World, Learning Technologies Conference).
  • Participating in online courses or bootcamps to deepen skills in advanced statistics, machine learning, or cloud-based data platforms (e.g., Coursera, edX, DataCamp).
  • Contributing to relevant open-source projects or maintaining a public portfolio of analytical work (e.g., GitHub, Tableau Public).
  • Reading academic journals or industry publications focused on learning science, organisational psychology, or HR research to stay current with best practices.
  • Joining professional networks or communities of practice for learning analytics or people analytics professionals to share insights and learn from peers.

10How the AI economy is changing work like this

Before we ask anything of you, here's what we can already say about AI and work of this kind:

The new skill this role is being asked for: Prompt Engineering & LLM Integration for Analytics

Competitors are already using Large Language Models (LLMs) to draft reports in 10 minutes that used to take 2 hours. Analysts who figure this out will outproduce peers 3:1. This isn't just about ChatGPT; it's about integrating these tools into your workflow.

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

Your PlanIllustration

Built for Senior Global Learning Analytics Manager

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

  1. Data analysis and designPearson Education Ltd · covers 5 of 10 standardsLevel 5
  2. Data AnalyticsPearson Education Ltd · covers 5 of 10 standardsLevel 5
  3. Data Analytics PrimerNOCN · covers 6 of 10 standardsLevel 4
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.

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.

Prompt Engineering & LLM Integration for Analytics

Competitors are already using Large Language Models (LLMs) to draft reports in 10 minutes that used to take 2 hours. Analysts who figure this out will outproduce peers 3:1. This isn't just about ChatGPT; it's about integrating these tools into your workflow.

  • Context Windows & Token Limits
  • Temperature Settings for Tasks
  • RAG (Retrieval Augmented Generation)
  • Output Validation & Hallucination Detection
  • Prompt Chaining for Complex Analysis

Advanced Causal Inference & Quasi-Experimental Design

Leaders are tired of 'correlation isn't causation' caveats. The demand for proving *causal* impact of learning programmes is only growing. Simply showing a link isn't enough; you'll need to demonstrate genuine impact.

  • Difference-in-Differences (DiD)
  • Regression Discontinuity Design (RDD)
  • Propensity Score Matching (PSM)
  • Instrumental Variables (IV)
  • Synthetic Control Methods

What you’ll use

Skills this role draws on

Technical

  • Kirkpatrick Model of Evaluation (Level 1-4)
  • Learning Transfer Analysis
  • Skills Taxonomy & Ontology Design
  • Predictive Modelling for Learning Outcomes
  • Learning Experience Data Governance (xAPI/cmi5)

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

    Learning Data Analyst (Level 002)

    3-5 years

    Skills to master

    • Independently handling ad-hoc data requests, building reliable dashboards, conducting descriptive analysis, and beginning to identify patterns in learning data. You'll have mastered SQL and a BI tool.

    You're ready to move on when

    • Consistently delivers accurate and timely analyses without heavy supervision.
    • Proactively identifies data quality issues and proposes solutions.
    • Begins to translate basic data findings into simple, actionable insights for L&D stakeholders.
    • Shows initiative in learning new analytical techniques and tools.
  2. 2

    Data Scientist (from another domain)

    5-7 years

    Skills to master

    • Transferring core data science skills (e.g., machine learning, statistical modelling, programming) to the unique context of learning and HR data. You'll need to quickly learn about learning science and HR processes.

    You're ready to move on when

    • Demonstrable experience building and deploying predictive models in previous roles.
    • Strong programming skills in Python or R for statistical analysis.
    • A genuine interest in human behaviour, learning, and talent development.
    • Ability to quickly grasp new domain knowledge and apply analytical frameworks to it.
  3. 3

    HR Analyst / People Analyst

    4-6 years

    Skills to master

    • Deepening technical skills in SQL and Python, moving beyond standard HR reporting to more advanced statistical analysis and predictive modelling. Specialising in the learning domain.

    You're ready to move on when

    • Strong understanding of HR data structures and common HR metrics.
    • Experience with HRIS reporting and data extraction.
    • A clear desire to specialise in learning and development analytics.
    • Proactive in learning advanced analytical techniques and tools.

11Where this role leads

The long view:Your journey here is really what you make of it. We'll give you the tools, the challenges, and the support, but your ambition and drive will ultimately shape where you go. This Senior Learning Analytics Manager role is a fantastic stepping stone to a truly impactful career in people data.

Pay & demand

Pay and demand for this role will appear here, each figure traced to a named authoritative source (e.g. the ONS Annual Survey of Hours and Earnings, under the Open Government Licence). We don’t show numbers we can’t attribute.

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 Senior Global Learning Analytics Manager is actually changing. In about two minutes, the free confidence check asks where you stand on each of the ten. That's the whole check, and it's what makes the plan yours rather than generic.

Where it leads

Roles this leads to

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

  • Global Learning Analytics Manager Manager (Level 005)

12The team that's yours

No two people are taught the same way. This is one-to-one, not one-to-many.

Zavmo is a hyper-personalised AI learning platform. Twelve virtual tutors, each with a different way of teaching, and one orchestration agent that picks the right one for the moment. So every single lesson is shaped around you, your role, and the way you learn. Not a course everyone sits through. A conversation built for you, and no one else.

…and nine more, matched to you after your first chat. Meet all twelve

Start free and meet yours

13What it feels like

A conversation, not a course

Because your tutor knows your role, your projects and your last session, learning sounds like this. And it's different for every single person:

Data analysis and designLevel 5

Applied to your work in Senior Global Learning Analytics Manager

This unit aims to equip learners with the ability to analyse data using various techniques, design data analysis solutions tailored to specific requirements, and evaluate data quality using appropriate metrics. Learners will also understand data presentation methods and be able to interpret data analysis results to draw meaningful conclusions.

How the thinking builds
  1. Remember
  2. Understand
  3. Apply
  4. Analyse
  5. Evaluate
  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.

One to one, not one to many

No two people run this the same way

A course is written once and handed to everyone. This is assembled around you, and keeps changing as it learns you. Five things it reads, and what each one changes.

  1. Your actual work Every lesson is taught against a live piece of your own work, not a worked example from a textbook.
  2. What you already know The first conversation finds your starting point, so you skip what you can already do and spend the time on what you cannot.
  3. The conditions you learn under Not a learning-styles quiz. The evidence does not support those. The dimensions the research does back, read once and used to shape the plan.
  4. How far you got last time It picks up mid-thought. The tutor knows what you said, what you struggled with, and what it asked you to try.
  5. Which tutor suits the moment Twelve of them, each for a different kind of thinking. The one who walks you through a first idea is not the one who stress-tests it.

See how you learn, free. Eight questions, no sign-up. A directional taster; the diagnostic inside Zavmo goes deeper and keeps adapting.

DemonstrateIllustration

Evidenced on your work in Senior Global Learning Analytics Manager

You do not finish by watching something. You finish by showing it on the work you already do, against the measures this job is judged on.

  • Project Completion & ImpactSuccessfully delivering complex analytical projects that address key L&D or business questions.Delivered a skills gap analysis that led to a £150,000 reallocation of L&D budget to critical emerging skills, completed within the agreed 10-week timeline.85% of assigned projects completed on time and delivering actionable insights.
  • Insight Adoption RateHow often your analytical recommendations are actually taken up and acted upon by L&D leadership or business partners.Your analysis showed that a particular compliance training wasn't reducing incidents. L&D then redesigned the programme based on your findings, leading to a 10% drop in reported incidents.60% of key recommendations result in a measurable change in L&D strategy or programme design.
  • Mentee Development & RetentionThe growth and engagement of any junior analysts you're informally mentoring.Helped a junior analyst improve their SQL skills to the point where they could independently build a new data extract, and they expressed high job satisfaction.At least one mentee shows significant progress (e.g., takes on more complex tasks, improves code quality) within 12 months, and remains with the team.
  • Data Quality ImprovementIdentifying and helping to resolve underlying data quality issues across our learning and HR systems.Worked with IT to fix an issue where 5% of learning completion data was not syncing correctly from the LMS, ensuring more accurate reporting for all future analyses.Reduce identified critical data errors by 20% across key L&D datasets annually.
These are this job's own measures, with its own targets. Nothing is marked evidenced, because nobody has started this yet. Yours would fill in from the work you bring.

Your passport

This isn't a certificate you file away. It's a passport to the life you're designing.

Every credit you earn and every fluency you build adds up: evidence where it counts, carried with you. Zavmo keeps the map: where you are, where you're heading, and the next step, at your pace, around your life. From Senior Global Learning Analytics Manager to Lead Learning Analytics Consultant (Level 004), and whatever you decide comes after.

Level 5 · in progressAI Fluency→ Lead Learning Analytics Consultant (Level 004)→ your design
Where this takes you

Your journey here is really what you make of it. We'll give you the tools, the challenges, and the support, but your ambition and drive will ultimately shape where you go. This Senior Learning Analytics Manager role is a fantastic stepping stone to a truly impactful career in people data.

See Your Progress GrowIllustration
Senior Global Learning Analytics Manager
  • Kirkpatrick Model of Evaluation (Level 1-4)
  • Learning Transfer Analysis
  • Skills Taxonomy & Ontology Design
  • Predictive Modelling for Learning Outcomes
  • Learning Experience Data Governance (xAPI/cmi5)
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.

14The 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

Senior Global Learning Analytics Manager is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. Lead Learning Analytics Consultant (Level 004)

    3-5 years

    One level up (L3 to L4)

    • Enterprise Data Architecture for L&D: Designing ETL/ELT pipelines and data warehousing solutions.
    • Advanced Statistical Consulting: Acting as the go-to expert for complex statistical challenges across the business.
    • Vendor Management (Data Focus): Evaluating and managing data-related vendors and partnerships.
    • Budget Management (up to £500K): Owning the budget for analytical tools, data sources, and team resources.

  2. Global Learning Analytics Manager Manager (Level 005)

    5-7 years

    Two levels up (L3 to L5)

    • Advanced Data Governance Strategy: Defining and implementing enterprise-wide data governance for people data.
    • Strategic Platform Evaluation: Making decisions on enterprise BI and data warehousing platforms.
    • External Representation: Representing the organisation at industry conferences and thought leadership events.
    • Innovation Portfolio Management: Overseeing a portfolio of analytical innovation projects.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, a big chunk of your week is probably spent on tasks that, while necessary, aren't the most exciting. Imagine getting back 10-15 hours every week to focus on the really meaty, strategic analytical challenges. That's what AI can do for you in this role.

We're not talking about replacing your brain; we're talking about giving you a seriously powerful assistant. Our AI Productivity Hub is designed to help you automate the tedious, speed up your research, and even help you draft those tricky executive summaries. Think of it as your secret weapon to become an even more impactful Senior Learning Analytics Manager.

Automated Data Harmonization

Use AI scripts to automatically clean, map, and merge disparate datasets from the LMS (Cornerstone), HRIS (Workday), and engagement surveys (Qualtrics). It'll flag anomalies for your human review, but it'll do the grunt work of getting your data ready for analysis in a fraction of the time.

Thematic Feedback Analysis

Feed thousands of open-ended comments from course feedback surveys ('smile sheets') into an LLM. It'll instantly identify and quantify key themes, sentiment, and actionable suggestions, replacing hours of manual reading and categorisation. You'll get insights from qualitative data much faster.

Pre-Meeting Research Synthesis

Need to quickly get up to speed on a new topic for a high-stakes meeting? Ask an AI assistant to 'Summarise the top 5 academic papers from the last 3 years on measuring learning transfer for soft skills'. You'll get instant domain expertise, saving you hours of digging through journals.

Executive Summary Drafting

After creating a complex dashboard in Tableau, paste screenshots or key data points into an LLM. Prompt it to 'Write a 3-bullet point executive summary for a CHRO explaining the key insights and recommended actions from this data.' It'll give you a solid first draft, freeing you up to refine the message.

Common questions

Common questions

How do you become a Senior Global Learning Analytics Manager?

Common routes in include Learning Data Analyst (Level 002) (3-5 years), Data Scientist (from another domain) (5-7 years) and HR Analyst / People Analyst (4-6 years). Times vary with prior experience.

Where can a Senior Global Learning Analytics Manager progress to?

This role can lead on to Lead Learning Analytics Consultant (Level 004) (3-5 years) and Global Learning Analytics Manager Manager (Level 005) (5-7 years), depending on the skills you build.

What level is a Senior Global Learning Analytics Manager in the UK?

This role aligns to RQF Level 5 on the UK framework, a guide to the depth of qualification it maps to, not a hard entry bar.

What new skills matter most for a Senior Global Learning Analytics Manager?

Increasingly, Prompt Engineering & LLM Integration for Analytics and Advanced Causal Inference & Quasi-Experimental Design. These are the areas where the higher-paid, future-proof work is heading.

The honest bit

You’ve started things before

Most of them were built for a room full of people who aren’t you. A cohort moves on whether or not your week allowed it, and by the third week the thing you’re behind on becomes the reason you stop opening it.

There’s no cohort here, and no timetable to fall behind. Before anything starts, Zavmo asks when you’re sharpest and how long you can realistically sit down for, then builds the sessions around those answers. A bad fortnight changes your pace. It doesn’t put you behind.

And you only pay once you start learning. Searching and planning are free, and you can cancel any time — so the cost of finding out is an afternoon, not a year.

What it costs

Less than one coaching session. Every month.

A single career-coaching hour costs more than a month of this, and it ends when the hour does. Zavmo doesn't. It's £70 a month, about £2.30 a day, for a companion that knows a Senior Global Learning Analytics Manager, works on the job you actually do, and keeps going at your pace rather than a timetable's.

  • Searching and planning stay free. You only pay when you start learning.
  • Your credits are yours. Regulated, and they don't vanish when a subscription ends.
  • Cancel any time and billing stops. No notice period, no minimum term.

Your path, personalised

You have the map. Walking it is the part we do together.

This route runs to 10 national skill standards. That is a real journey.

Zavmo shapes a learning experience as unique as you are. It fits how you learn, your pace and the work you already do. Every step stays benchmarked to recognised national standards. That’s the plan for becoming a Senior Global Learning Analytics Manager: personal to you, and it still counts. The first steps are free.

Independent research finds well-designed intelligent tutoring performs nearly as well as one-to-one human tutoring: VanLehn (2011), Educational Psychologist.

A private tutor in the UK averages £35–40 an hour . Zavmo is £70/month.

A real plan on learn.zavmo.ai: Ofqual-regulated units, credits, and a three-month run at your own pace.
Start free No commitment. See your first steps free.

15Where 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.

Other roles in Learning and Development

Stay in the field you know and move sideways rather than up.

If you leave this industry

The skills you'll build here are highly transferable. You could move into broader People Analytics roles, Data Science leadership positions in other industries (e.g., marketing analytics, product analytics), or even consulting roles specialising in HR/Learning transformation. The demand for data-savvy leaders is only growing.

Not sure this is the right direction?

Work out what you actually want from work first, then come back and see which roles fit it. Takes about ten minutes.

This role profile is © 2026Growth 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. Build my plan, free Here's the first ten minutes: a 2-minute confidence check → your personalised roadmap → meet the tutors matched to you. No card, cancel any time. 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.