UK

United Kingdom · Learning and Development · Entry Level (0-2 years)

Learning Analytics Associate

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 bandEntry Level (0-2 years)
  • Direct reportsNo direct reports
  • Reports toLearning Analytics Analyst
  • UK framework levelUsually someone starting out, or keeping a process running

Also advertised as Junior L&D Analyst · Training Data Assistant · L&D Reporting Support

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 Learning Analytics Associate

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

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1What this role really is

This role is all about getting stuck into the raw data from our learning platforms and HR systems. You'll be the person pulling the numbers, cleaning them up, and making sure they're accurate before anyone else sees them. Think of yourself as the foundational layer for all our learning insights—if your data isn't spot on, everything built on top of it falls apart. It's a hands-on role, perfect if you love digging into spreadsheets and solving data puzzles.

2What you'd actually use

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

Microsoft ExcelIntermediate

Cleaning raw data, using PivotTables for summaries, applying VLOOKUP/INDEX-MATCH for combining datasets, and writing basic formulas to calculate metrics. This is your bread and butter.

Workday HCM / SAP SuccessFactors (HRIS)Basic

Pulling standard reports on employee demographics, tenure, and basic performance ratings. You'll navigate the user interface with guidance, following existing report templates.

Cornerstone OnDemand / Degreed (LMS/LXP)Basic

Running pre-built reports on course completions, enrollments, and 'seat time'. You'll be manually exporting CSVs for further analysis in Excel, following a clear process.

Tableau Desktop / Power BI DesktopBasic

Connecting to Excel/CSV files, refreshing existing dashboards, and making minor adjustments to charts based on feedback. You'll learn to build simple bar/line charts from established templates.

SQL (PostgreSQL / T-SQL)Basic

Running basic `SELECT`, `FROM`, `WHERE` clauses to query clean, well-documented tables under supervision. You'll be using pre-written queries and making small modifications.

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
Data Extraction MethodFollow established guides; escalate if a new data source is needed or a guide doesn't exist.Choose the most efficient method (e.g., API vs. manual export) for routine tasks; consult on novel data sources.Design and implement new data extraction pipelines; define best practices for data acquisition.
Data Cleaning RulesApply predefined cleaning rules; escalate any ambiguous data points or new types of errors.Develop and propose new cleaning rules for common issues; implement with manager approval.Establish enterprise-wide data quality standards and governance policies for learning data.

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.

Report Accuracy
The percentage of standard data pulls and reports that are free from errors when compared to the source system.
Target · >98% accuracy

You pull a list of course completions for the Sales team. Your manager checks 10 random entries against the LMS and finds no discrepancies. That's 100% accuracy for that check.

Data Request Turnaround Time
How quickly you can fulfil standard, routine data requests from the L&D team.
Target · Within 48 hours for standard requests

An L&D Programme Manager asks for a list of everyone who completed 'Leadership Fundamentals' last quarter. You deliver it within 36 hours, well within the target.

Data Cleaning Efficiency
The proportion of identified data inconsistencies that you successfully resolve or flag for resolution.
Target · Resolve/flag 95% of identified issues

You find 50 entries where a learner's department is missing. You update 48 of them and flag the remaining 2 for your manager because you can't find the information. That's 96% resolved/flagged.

Adherence to Data Governance
How well you follow our established rules and processes for handling, storing, and sharing sensitive learning data.
  • No data breaches or accidental sharing of sensitive information. All data stored in correct locations. Regular participation in data governance training. Your manager doesn't need to chase you for correct file naming conventions.
Proactive Issue Identification
Your ability to spot potential data problems or inconsistencies before they become bigger issues.
  • You flag unusual trends in report numbers (e.g., a sudden drop in completions that doesn't make sense). You notice a common data entry error pattern and bring it to your manager's attention. You ask 'why does this number look odd?' before being told to.
Team Collaboration & Learning
How effectively you work with your immediate team, ask for help when needed, and absorb new knowledge.
  • You actively participate in team meetings. You ask clear, thoughtful questions when you're stuck, rather than struggling in silence. You apply feedback from your manager to your next piece of work. You offer to help others when your own tasks are complete.

5Would you like it

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

What people enjoy
Solving Puzzles

You enjoy the challenge of taking disparate, messy data and making sense of it. Finding that one missing piece of data or fixing a tricky formula gives you a real buzz.

Spending an afternoon tracking down why 10 learners' completion statuses weren't updating in the LMS, eventually finding a tiny configuration error, and fixing it.

Learning and Growing

You're keen to pick up new tools (like SQL or advanced Excel functions) and understand how data helps a business. You actively seek feedback and opportunities to expand your skills.

Volunteering to take an online course on Power Query after seeing your manager use it, then applying what you've learned to automate a manual report.

Making a Real Impact (indirectly)

While you're not directly designing training, you get satisfaction from knowing your accurate data helps the L&D team create better programmes that genuinely help people develop.

Seeing a report you helped prepare being used in a presentation to justify investment in a new leadership programme, knowing your numbers were the foundation.

What frustrates people
  • Dealing with legacy systems that are clunky and slow to extract data from.
  • Spending hours cleaning data only for new inconsistencies to appear next week.
  • Being asked for 'just a quick report' that actually requires hours of data wrangling.
  • Trying to find the 'right' data when it's scattered across multiple, disconnected platforms.
  • The constant battle between what data we *want* and what data we can *actually* get.
What this role does not give you
  • Direct programme design or delivery responsibilities.
  • High-level strategic decision-making in L&D (not yet, anyway).
  • A role where you avoid repetitive data cleaning tasks.
  • Immediate, high-visibility impact on every project you touch.

6Who you work with

Your work directly underpins the integrity of all learning data. Accurate data means we can make informed decisions about where to invest our training budget, which programmes to scale, and how to help our employees grow. If the data you provide is flawed, it can lead to misinterpretations of learning effectiveness, potentially misdirecting significant L&D resources and impacting employee development strategies.

Inside the business
  • Learning Analytics Analyst (your direct manager)
  • Senior Learning Analytics Analyst
  • L&D Programme Managers (who run the training)
  • HR Business Partners (who care about employee development)
  • IT Support (when systems play up)

7What you need before you start

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

  • Strong numerical aptitude and comfort working with large datasets.
  • Proven ability to learn new software and technical skills quickly.
  • Experience (even from university projects or internships) with data entry, cleaning, or basic reporting.
  • Excellent organisational skills – you can keep track of multiple tasks and deadlines.
  • A genuine interest in how data can improve learning and development.

8What to practise next

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

Advanced Excel & Power Query

While SQL and BI tools are great, Excel isn't going anywhere. Mastering Power Query will allow you to automate data cleaning and transformation tasks that currently take hours, freeing you up for more analytical work. It's a huge productivity booster.

M language basics · Automated data refresh · Complex data transformations

  • This week: Watch a few YouTube tutorials on Power Query basics.
  • This month: Try to automate one of your most repetitive Excel data cleaning tasks using Power Query.
  • Month 2: Experiment with connecting Power Query to a web source or a simple database.
  • Month 3: Share your automated solution with your team and explain how it works.

Quick win: Find one CSV file you regularly clean manually and try to build a Power Query script to do it for you.

Intermediate SQL

As you progress, you'll need to pull data directly from databases, not just rely on pre-built reports. A solid grasp of SQL will give you much more flexibility and control over the data you extract, letting you answer more complex questions.

JOIN operations · GROUP BY and aggregate functions · Window functions

  • This week: Complete an online SQL tutorial (e.g., SQL Zoo, Codecademy).
  • This month: Practice writing `JOIN` queries on a dummy database or our internal sandbox environment.
  • Month 2: Try to rewrite one of your complex Excel analyses using SQL instead.
  • Month 3: Ask your manager for a real-world data question that could be answered with an intermediate SQL query.

Quick win: Start by understanding the structure of our key database tables. Just knowing what's where is a massive head start.

9Staying current once you are in

What people here do to keep up
  • Online courses on data cleaning and manipulation in Excel or Python (e.g., DataCamp, Coursera).
  • Participating in internal L&D 'lunch and learn' sessions to understand our programmes better.
  • Attending webinars or reading articles on basic learning analytics concepts and metrics.
  • Shadowing a more senior analyst to see how they approach complex data problems.
  • Joining internal data communities or forums to 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 (Basic)

AI tools are becoming ubiquitous. Being able to ask the right questions to get useful answers from large language models (LLMs) will significantly speed up your work, from drafting summaries to generating initial code snippets. Analysts who master this will be far more productive.

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

Your PlanIllustration

Built for Learning Analytics Associate

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

  1. Data analysis and data structure design 3Cambridge OCR · covers 1 of 10 standardsLevel 2
  2. Data Analytics PrimerNOCN · covers 5 of 10 standardsLevel 4
  3. Data AnalyticsPearson Education Ltd · covers 4 of 10 standardsLevel 4
  4. Data AnalysisBCS, The Chartered Institute for IT · covers 2 of 10 standardsLevel 4
  5. Data analysis and designPearson Education Ltd · covers 4 of 10 standardsLevel 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.

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 (Basic)

AI tools are becoming ubiquitous. Being able to ask the right questions to get useful answers from large language models (LLMs) will significantly speed up your work, from drafting summaries to generating initial code snippets. Analysts who master this will be far more productive.

  • Clear, concise prompting
  • Context & constraints
  • Iterative prompting
  • Output validation

Data Governance (Practical Application)

As data becomes more central, ensuring its quality, security, and ethical use is paramount. You'll be on the front lines, so understanding the 'why' behind our rules will help you apply them consistently and spot issues early.

  • Data quality rules
  • Data lineage
  • Data privacy principles
  • Metadata management

What you’ll use

Skills this role draws on

Technical

  • Kirkpatrick Level 1 & 2 Understanding
  • Basic Data Storytelling
  • Learning Transfer Awareness

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

    Data Entry / Administrative Assistant

    1-2 years

    Skills to master

    • Exceptional attention to detail, strong organisational skills, basic Excel proficiency, understanding of data integrity.

    You're ready to move on when

    • You're already spotting errors in data you're entering and suggesting improvements.
    • You've taken initiative to automate small, repetitive tasks using Excel formulas.
    • You've expressed a clear interest in moving into a more analytical role.
  2. 2

    Internship in Analytics / L&D

    6-12 months

    Skills to master

    • Exposure to real-world data challenges, understanding of business context, basic reporting tools, professional communication.

    You're ready to move on when

    • You've successfully completed an analytical project during your internship.
    • You've received positive feedback on your data accuracy and problem-solving.
    • You've built a small portfolio of analytical work, even if it's from university.
  3. 3

    Recent Graduate (Numerate Degree)

    0-1 year (direct entry)

    Skills to master

    • Academic understanding of statistics/data, research methodology, critical thinking, presentation skills.

    You're ready to move on when

    • You achieved good grades in quantitative subjects.
    • You can articulate how your academic projects relate to business data challenges.
    • You're eager to apply theoretical knowledge to practical, messy datasets.

11Where this role leads

The long view:Your journey starts here, with a solid foundation in learning data. We're excited to see how you grow and contribute to making learning more effective and impactful for everyone at Zavmo.

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 Learning Analytics Associate 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

The record names a next step, but the catalogue has no page for it yet:

  • Learning Analytics Analyst (Level 2)

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 data structure design 3Level 2

Applied to your work in Learning Analytics Associate

This unit aims to provide learners with an understanding of data analysis techniques and data structure design principles. Learners will be able to analyse data to identify patterns and insights, design effective data structures, and present data analysis findings clearly using appropriate visualisations and reporting methods.

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 Learning Analytics Associate

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.

  • Report AccuracyThe percentage of standard data pulls and reports that are free from errors when compared to the source system.You pull a list of course completions for the Sales team. Your manager checks 10 random entries against the LMS and finds no discrepancies. That's 100% accuracy for that check.>98% accuracy
  • Data Request Turnaround TimeHow quickly you can fulfil standard, routine data requests from the L&D team.An L&D Programme Manager asks for a list of everyone who completed 'Leadership Fundamentals' last quarter. You deliver it within 36 hours, well within the target.Within 48 hours for standard requests
  • Data Cleaning EfficiencyThe proportion of identified data inconsistencies that you successfully resolve or flag for resolution.You find 50 entries where a learner's department is missing. You update 48 of them and flag the remaining 2 for your manager because you can't find the information. That's 96% resolved/flagged.Resolve/flag 95% of identified issues
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 Learning Analytics Associate to Learning Analytics Analyst (Level 2), and whatever you decide comes after.

Level 2 · in progressAI Fluency→ Learning Analytics Analyst (Level 2)→ your design
Where this takes you

Your journey starts here, with a solid foundation in learning data. We're excited to see how you grow and contribute to making learning more effective and impactful for everyone at Zavmo.

See Your Progress GrowIllustration
Learning Analytics Associate
  • Kirkpatrick Level 1 & 2 Understanding
  • Basic Data Storytelling
  • Learning Transfer Awareness
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

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

  1. Learning Analytics Analyst (Level 2)

    2-3 years in the Associate role

    You'll move from executing tasks under close supervision to owning complete analytical projects from start to finish. You'll be making more independent decisions on methodology and tool usage.

    • Intermediate SQL: Writing more complex queries with joins and aggregations.
    • Power Query (M language): Automating data cleaning and transformation pipelines.
    • Survey Design & Analysis: Designing effective surveys and analysing open-text feedback.
    • Kirkpatrick Level 3 & 4 Concepts: Beginning to explore how to measure behaviour change and business impact.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, a lot of the initial grunt work in data analysis can be automated. We're not just talking about using AI; we're talking about making your job easier and letting you focus on the interesting stuff, faster. Imagine less time wrestling with messy spreadsheets and more time actually understanding what the data means.

In Learning Analytics, AI isn't just a buzzword; it's a practical helper. It can take the sting out of repetitive tasks, help you spot patterns you might miss, and even draft your initial communications. We're building an AI-first culture here, and we want you to be part of it from day one. Here's how AI will actually help you in this role:

Thematic Analysis Assistant

Feed thousands of open-ended comments from 'smile sheets' (our Level 1 feedback surveys) into an AI. It'll instantly categorise feedback into themes like 'Instructor Quality', 'Content Relevance', or 'Platform Issues', saving you hours of manual reading. You'll then validate the AI's work, not do it all from scratch.

Automated Report Drafter

Connect AI tools to your basic data outputs (like a simple Excel summary) and get a first draft of a weekly or monthly narrative summary. It'll highlight key trends, outliers, and changes, giving you a solid starting point for your reports, meaning less time staring at a blank page.

Stakeholder Comms Co-Pilot

Got a simple data finding, like 'Course X completion rates dropped by 10% this month'? Ask an AI to draft a clear, jargon-free email to an L&D Programme Manager explaining what this means and suggesting a follow-up. It's great for getting those initial communications out quickly and clearly.

SQL Query Co-Pilot

Use AI assistants (like GitHub Copilot) to translate natural language requests ('Show me all employees who completed the sales training and their quota attainment for the next quarter') into a valid SQL query. This accelerates your data exploration, letting you get the data you need much faster, even with basic SQL knowledge.

Common questions

Common questions

How do you become a Learning Analytics Associate?

Common routes in include Data Entry / Administrative Assistant (1-2 years), Internship in Analytics / L&D (6-12 months) and Recent Graduate (Numerate Degree) (0-1 year (direct entry)). Times vary with prior experience.

Where can a Learning Analytics Associate progress to?

This role can lead on to Learning Analytics Analyst (Level 2) (2-3 years in the Associate role), depending on the skills you build.

What level is a Learning Analytics Associate in the UK?

This role aligns to RQF Level 2 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 Learning Analytics Associate?

Increasingly, Prompt Engineering (Basic) and Data Governance (Practical Application). 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 Learning Analytics Associate, 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 Learning Analytics Associate: 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 2

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 gain in this role—data cleaning, analysis, visualisation, and storytelling—are highly transferable. You could move into broader HR Analytics, People Analytics, or even other data analyst roles in areas like Marketing, Finance, or Operations, both within our company or in other industries. Data is everywhere!

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.