UK

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

Senior Performance Analytics Assistant

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 bandSenior (5-8 years)
  • Direct reportsNo direct reports
  • Reports toManager, Learning Analytics & Insights
  • UK framework levelUsually a professional owning their own work, or leading a small team

Also advertised as Senior Learning Data Analyst · L&D Insights Specialist · Senior Learning Effectiveness Analyst

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

NOCN Level 4 certificate for Data Analysts NOCN · Level 4 · covers 7 of 10 standards
Pearson BTEC Level 5 Higher National Diploma in Computing for England Pearson Education Ltd · Level 5 · covers 4 of 10 standards
Pearson BTEC Level 4 Higher National Certificate in Computing for England Pearson Education Ltd · Level 4 · covers 3 of 10 standards
Pearson BTEC Level 5 Higher National Diploma in Digital Technologies Pearson Education Ltd · Level 5 · covers 2 of 10 standards
Highfield Level 3 Diploma for Team Leaders and Supervisors (RQF) Highfield Qualifications · Level 3 · covers 2 of 10 standards
OTHM Level 7 Diploma in Data Science OTHM Qualifications · Level 7 · covers 4 of 10 standards

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

The units you would start with

Data Analytics Primer NOCN Level 4 certificate for Data Analysts
Data Analytics Pearson BTEC Level 5 Higher National Diploma in Computing for England
Data Analysis Highfield Level 3 Diploma for Team Leaders and Supervisors (RQF)
Data Analysis and Visualisation OTHM Level 7 Diploma in Data Science

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
Systems Fluency seeing the whole picture
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Your Plan Illustration

Built for Senior Performance Analytics Assistant

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

  1. Data Analytics Primer NOCN · covers 7 of 10 standards Level 4
  2. Data Analytics Pearson Education Ltd · covers 4 of 10 standards Level 5
  3. Data Analysis Highfield Qualifications · covers 2 of 10 standards Level 3
  4. Data Analysis and Visualisation OTHM Qualifications · covers 4 of 10 standards Level 7
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 Senior Performance Analytics Assistant?

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

  • Prompt Engineering & LLM Integration
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 Senior Performance Analytics Assistant 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

Analyses data to find out what works in training and development, and what doesn't. You dig into why a training programme didn't land, or prove that another one made a real difference to the business, turning messy information into clear findings.

4What you'd actually use

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

Workday HCM / SAP SuccessFactors Advanced

Building complex custom reports using the native report writer, understanding the data model to join learning and talent data effectively, and troubleshooting data discrepancies.

Cornerstone OnDemand / Degreed Advanced

Using advanced reporting features, scheduling automated reports, and beginning to use API connectors to pull data directly into our data warehouse for deeper analysis.

Tableau Desktop / Power BI Premium Advanced

Writing complex calculations (LOD Expressions, DAX), designing and publishing interactive dashboards to the server for business users, and optimising existing dashboards for performance.

Excel (Power Query & VBA) Expert

Expertly using Power Query (M language) for automating data cleaning pipelines, building robust data models, and writing simple VBA macros to automate repetitive tasks. Yes, we still use Excel for certain things, and you'll be the expert.

SQL (PostgreSQL / T-SQL) Advanced

Writing complex multi-table JOINs, GROUP BYs, and window functions to extract, transform, and clean data directly in the database. You'll be profiling data and preparing it for analysis.

Qualtrics / Glint Advanced

Designing effective surveys, analysing open-text feedback using advanced techniques, and correlating survey results with behavioural data from other systems.

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
Analytical Methodology for a new L&D programme evaluation Proposes a method to their supervisor for review and approval; executes under close guidance. Selects a method from established options; seeks manager feedback on complex variations; executes independently. Designs and justifies the most appropriate methodology, including quasi-experimental approaches, for complex, ambiguous questions; consults Manager on significant deviations from standard practice; mentors juniors on best practices.
Data Source Integration Strategy Identifies required data sources; asks supervisor for guidance on how to extract and join data. Independently extracts and joins data from 2-3 known sources; escalates issues with data quality or access. Designs strategy for integrating novel or challenging data sources (e.g., xAPI data from an LRS); profiles data quality and recommends cleaning approaches; consults Data Engineering on complex API integrations.
Prioritisation of ad-hoc requests vs. planned work Immediately escalates all ad-hoc requests to supervisor for prioritisation. Assesses urgency and impact of ad-hoc requests against current workload; proposes prioritisation to manager for approval. Independently prioritises most ad-hoc requests based on business impact and existing commitments; proactively communicates any impact on planned work; escalates only high-stakes conflicts to Manager.

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.

Automation Impact
Hours of manual reporting or data preparation saved each month through automation.
Target · Automate 20+ hours per month

You build a Power Query script that automatically cleans and joins LMS and HRIS data, saving the team 25 hours of manual spreadsheet work each month. That's a win!

Complex Project Delivery Rate
Percentage of complex analytical projects delivered on or before the agreed timeline.
Target · 90% of projects delivered on time

You took on an analysis of leadership training's impact on team retention, which involved joining five different datasets. You delivered the final report and presentation within the 8-week timeframe we agreed.

Insight Adoption Rate
Number of L&D strategic decisions or programme changes directly influenced by your analytical findings.
Target · Influence 2-3 key decisions per quarter

Your analysis showed that our onboarding programme wasn't actually improving new hire productivity. Based on your report, the L&D team completely redesigned the programme, leading to better results.

Analytical Rigour & Methodology
The soundness and robustness of your analytical approaches, especially when dealing with complex, ambiguous questions.
  • Your analyses are rarely challenged on their methodology. You can clearly explain your assumptions and limitations. You proactively identify potential biases in the data or approach. You're the person others come to when they need to sanity-check their own analysis.
Data Storytelling & Influence
Your ability to translate complex data findings into clear, compelling narratives that resonate with non-technical business leaders and drive action.
  • Your presentations are consistently praised for their clarity and impact. Business leaders reference your insights in their own discussions. You get invited to strategic planning meetings because people trust you to tell them what the data really means. People actually do things based on your recommendations.
Mentorship & Knowledge Sharing
The effectiveness of your informal guidance and support for junior analysts on the team.
  • Junior team members regularly seek your advice. Their work quality visibly improves after you've reviewed it or coached them. You actively contribute to our team's best practices and documentation, making it easier for everyone to learn and grow.

7Would you like it

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

What people enjoy
Solving Complex Puzzles

You love diving into a tangled mess of data, figuring out how different pieces fit together, and uncovering hidden patterns. The more ambiguous the problem, the more excited you get.

Being asked to figure out if our new leadership training actually reduced employee turnover, despite having incomplete data from three different systems. That's your kind of challenge.

Driving Real Impact

You're not content with just producing reports; you want to see your work lead to tangible changes. Knowing that your analysis helped improve a training programme or saved the company money really gets you going.

Seeing the L&D team completely redesign a core programme based on your findings, and then seeing the positive results in subsequent data. That's a huge win for you.

Mentoring & Developing Others

You enjoy sharing your knowledge and helping junior colleagues grow their skills. You get a kick out of seeing someone you've coached 'get it' and start producing great work on their own.

Spending an hour walking a junior analyst through a complex SQL query or helping them structure a presentation, and then seeing them confidently apply that knowledge later.

What frustrates people
  • Attribution vs. Causation Hell: You will constantly be asked to 'prove' a training programme caused a business outcome, when in reality, you can only show a correlation. Be prepared to defend your methodology against executives who want a simple, causal answer that doesn't exist.
  • The Data Silo Gauntlet: Your primary job is often being a data plumber, spending 60% of your time trying to join incomplete data from the LMS, the HRIS, a survey tool, and a separate performance system, none of which were designed to talk to each other.
  • Proxy Metric Purgatory: You want to measure on-the-job behaviour change, but you can't get the data. So you're forced to present weaker proxy metrics like course completion rates or manager satisfaction scores, knowing they don't tell the whole story.
  • The 'Urgent' Vague Request: Expect a weekly 'fire drill' from a senior leader asking you to 'just pull some numbers' to support a decision they've already made, requiring you to drop everything to find data that fits their narrative.
  • Lack of a Control Group: Unlike marketing, you can rarely run a true A/B test. You can't ethically withhold mandatory leadership or compliance training from a segment of the population to create a clean control group. It's just not how L&D works.
  • The 'Flavor of the Month' Initiative: You will invest weeks building a beautiful, automated dashboard for a major L&D programme, only for leadership to pivot to a new strategic priority three months later, rendering your work obsolete. It happens, unfortunately.
What this role does not give you
  • A perfectly clean, pre-joined dataset ready for analysis. You'll be doing a lot of the cleaning yourself.
  • A predictable, unchanging set of priorities. Things shift, and you'll need to roll with it.
  • The ability to always run true A/B tests with perfect control groups. You'll often be working with quasi-experimental designs.
  • A quiet, heads-down role with no stakeholder interaction. You'll be talking to people constantly.

8Who you work with

This role directly influences how we invest in our people. Your analysis helps us decide which learning programmes get funding, which ones need a rethink, and where we have critical skill gaps. Ultimately, you're helping us build a more capable, productive workforce, which is pretty fundamental to our overall business success.

Inside the business
  • L&D Business Partners (your primary internal clients)
  • Business Unit Leaders (who want to see impact)
  • HRIS Team (for core employee data)
  • Data Engineering Team (for data warehouse support)
  • HR Leadership Team (who set the overall people strategy)
Outside the business
  • LMS/LXP Vendors (for data access and reporting capabilities)
  • External Training Providers (for programme-specific data)

9What you need before you start

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

  • Proven experience (5-8 years) in a dedicated data analytics role, ideally within HR, L&D, or a related people function.
  • Demonstrable experience leading analytical projects from start to finish, including defining requirements, data acquisition, analysis, and presenting findings.
  • Strong proficiency in SQL for complex data querying and manipulation (you can write window functions in your sleep, probably).
  • Advanced skills in at least one major data visualisation tool (Tableau or Power BI), including dashboard design and complex calculations.
  • Expert-level Excel skills, particularly with Power Query for data automation.
  • A solid understanding of statistical concepts (e.g., correlation, regression, hypothesis testing) and their practical application to business problems.
  • Experience mentoring or guiding junior team members, even if informally.

10What to practise next

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

Advanced Statistical Modelling for Behavioural Data

Important within 12 months. As we get better data, we'll want to move beyond simple correlations to more robust predictive and causal models. Understanding techniques like multi-level modelling or survival analysis will be key to truly understanding learning impact over time.

Regression techniques (e.g., logistic, multi-level) · Survival analysis · Propensity score matching · Time-series analysis for learning trends

  • This quarter: Take an online course on advanced regression or statistical modelling (e.g., Coursera, edX).
  • Next quarter: Apply a new statistical technique to one of your existing datasets, even if it's just for internal experimentation.
  • Month 6: Present your findings from this new technique to the team, explaining the methodology and its implications.
  • Month 9: Explore using R or Python for statistical modelling, if you're not already comfortable with them.

Quick win: Start reading articles or watching YouTube tutorials on 'causal inference in HR' or 'predictive analytics for L&D'. Even a basic understanding will help you frame questions better.

11Staying current once you are in

What people here do to keep up
  • Actively participate in online data analytics communities or forums (e.g., Kaggle, Stack Overflow) to keep your skills sharp and learn from others.
  • Attend webinars or virtual conferences on People Analytics, L&D Measurement, or Data Storytelling to stay current with industry trends.
  • Contribute to internal knowledge sharing sessions, perhaps by presenting a new technique you've learned or a challenging project you've completed.
  • Take on a 'stretch' project that pushes your analytical boundaries, perhaps involving a new dataset or a more complex statistical method.

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.

Prompt Engineering & LLM Integration

Critical within 6 months—this is already happening, not future. Competitors are using tools like ChatGPT and Claude to draft reports in 10 minutes that used to take 2 hours. Analysts who figure this out will outproduce peers 3:1, and frankly, we need to keep up. It's about working smarter, not just harder.

  • Context windows and token limits
  • Temperature settings for different tasks
  • RAG (Retrieval Augmented Generation) architectures for proprietary data
  • Output validation and hallucination detection
  • Prompt chaining for complex analysis

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • Kirkpatrick & Phillips ROI Models
  • Learning Transfer Analysis
  • Skills Gap & Capability Forecasting
  • Experimental Design & Causal Inference

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

    Mid-Level Data Analyst (from any domain)

    3-5 years of prior experience

    Skills to master

    • Transitioning from general data analysis to the specifics of HR/L&D data, understanding people metrics, and developing strong stakeholder management skills within an HR context. You'll need to learn the 'language' of L&D.

    You're ready to move on when

    • Can independently lead an analytical project from start to finish.
    • Has experience cleaning and joining messy datasets from various sources.
    • Can present complex findings clearly to non-technical audiences.
    • Shows a genuine interest in learning about human capital and organisational development.
  2. 2

    L&D Specialist with Strong Data Skills

    5-7 years of prior L&D experience + 2-3 years of self-taught/formal analytics training

    Skills to master

    • Deepening technical skills in SQL, advanced Excel (Power Query), and data visualisation. Learning experimental design principles and how to apply them to learning programmes. You already know L&D
    • now you need the hardcore data chops.

    You're ready to move on when

    • Has a strong understanding of L&D programme design and delivery.
    • Can demonstrate proficiency in SQL and Power BI/Tableau.
    • Has actively sought out and completed analytics projects in previous L&D roles.
    • Is eager to move into a purely analytical role.
  3. 3

    Consultant (HR/Analytics Focus)

    3-6 years of prior consulting experience

    Skills to master

    • Adapting consulting frameworks to internal organisational challenges, building internal credibility, and focusing on long-term internal impact rather than project-based deliverables. You're used to client-facing work, now it's about internal clients.

    You're ready to move on when

    • Has a track record of delivering data-driven recommendations to clients.
    • Is comfortable with rapid problem-solving and presenting to senior leaders.
    • Can demonstrate strong technical analytical skills.
    • Is looking for a more stable, in-house role with deep impact.

15Where this role leads

The long view: This work can lead into people analytics or business intelligence roles, or towards managing a team that measures learning across an organisation.

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 Performance Analytics Assistant is actually changing.

Where it leads

Roles this leads to

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

  • Lead Learning Analytics Partner (Level 4)

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 Data Analytics Primer, worked against Senior Performance Analytics Assistant.

Data Analytics Primer Level 4

Applied to your work in Senior Performance Analytics Assistant

This unit aims to equip learners with a foundational understanding of data analytics, including its applications and the stages of the data analysis lifecycle. Learners will explore various data types and structures, understand the role of data within an organisation, and recognise the importance of GDPR and compliance requirements in data handling.

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 Senior Performance Analytics Assistant plan, free
See Your Progress Grow Illustration
Senior Performance Analytics Assistant
  • Kirkpatrick & Phillips ROI Models
  • Learning Transfer Analysis
  • Skills Gap & Capability Forecasting
  • Experimental Design & Causal Inference
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

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

  1. Lead Learning Analytics Partner (Level 4)

    2-4 years in current role

    This is a step up where you'll act as the primary analytics consultant for a specific business unit or a major L&D domain (e.g., Leadership Development). You'll be designing new data models and measurement strategies for key L&D programmes, and probably managing 1-2 junior analysts directly.

    • Data Architecture Design Contributing to the design of the L&D data schema within the enterprise data warehouse.
    • Advanced Predictive Modelling Building more sophisticated models to forecast skill gaps or predict learning outcomes.
    • Budget Management Managing small project budgets (e.g., for external data sources or tools, typically £50K-£100K).
    • Vendor Management Evaluating and working with external data/analytics vendors.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, a lot of the grunt work in analytics can be a bit of a slog. But what if you could offload the repetitive stuff and focus on the really interesting, high-impact analysis? That's where AI comes in.

For a Senior Performance Analytics Assistant, AI isn't about replacing your job; it's about making you incredibly more efficient and effective. Imagine spending less time wrestling with messy data or drafting emails, and more time uncovering those 'aha!' moments that truly shape our L&D strategy. Our internal AI Productivity Hub is packed with tools and guides to help you do just that.

Thematic Analysis Accelerator

Feed thousands of open-ended comments from course feedback surveys or qualitative interviews into an LLM. It'll instantly categorise feedback into themes like 'Instructor Quality', 'Content Relevance', and 'Platform Issues', saving you hours of manual coding. You'll get to the 'so what' much faster.

Automated Narrative Generation

Connect AI tools to your Tableau or Power BI dashboard and get a first draft of your weekly or monthly narrative summary. It'll highlight key trends, outliers, and deltas, giving you a solid starting point to refine and add your expert interpretation. No more staring at a blank page.

Stakeholder Comms Drafter

Got a complex finding, like 'Our new manager coaching programme is correlated with a 15% reduction in team regrettable attrition'? Ask an LLM to draft a clear, jargon-free email or presentation slide explaining what this means and why it matters to a specific business leader. It's like having a personal communications assistant.

SQL Query Co-Pilot

Use AI assistants (like GitHub Copilot or similar tools) to translate your 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 massively accelerates your data exploration and helps you write more complex queries faster, even with tricky joins.

Common questions

Common questions

How do you become a Senior Performance Analytics Assistant?

Common routes in include Mid-Level Data Analyst (from any domain) (3-5 years of prior experience), L&D Specialist with Strong Data Skills (5-7 years of prior L&D experience + 2-3 years of self-taught/formal analytics training) and Consultant (HR/Analytics Focus) (3-6 years of prior consulting experience). Times vary with prior experience.

Where can a Senior Performance Analytics Assistant progress to?

This role can lead on to Lead Learning Analytics Partner (2-4 years in current role), depending on the skills you build.

What new skills matter most for a Senior Performance Analytics Assistant?

Increasingly, Prompt Engineering & LLM Integration. These are the skills our record of this role lists as growing.

Free tools

Want a read on where you stand?

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

Read the Zavmo manifesto to understand how you will be taught Meet your tutors

Or try another one

17Where to go from here

Other roles at Level 4

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 skills involved, advanced analytics, data storytelling, working with complex behavioural data, and explaining findings clearly, transfer well. They can lead into broader people analytics roles, business intelligence, or product analytics in other industries. Translating data into clear insight is useful work in any sector.

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 Senior Performance Analytics Assistant 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.