UK

United Kingdom · Internal consulting · Mid-Level (2-5 years)

Analytics Solutions Consultant

As an Analytics Solutions Consultant, you transform chaotic data into clear business insights.

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.

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Free to start: a plan built for this role, and a Future Fluency module to try first. No card.

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Where should we send it?

One email: what AI is changing in this job, and where to start free. With a link back here. Nothing else follows unless you confirm your address.

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  • Experience bandMid-Level (2-5 years)
  • Direct reportsNo direct reports
  • Reports toSenior Analytics Solutions Consultant
  • UK framework levelUsually a coordinator, or early in a professional job

Also advertised as Data Insights Consultant · Business Intelligence Consultant · Junior Strategy Analyst (Data Focus) · Internal Data Consultant

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 5 of 8 standards
Pearson BTEC Level 4 Higher National Certificate in Computing for England Pearson Education Ltd · Level 4 · covers 3 of 8 standards
BCS Level 4 Diploma - Digital Modular Programme for Data Analysts BCS, The Chartered Institute for IT · Level 4 · covers 2 of 8 standards
Highfield Level 3 Diploma for Team Leaders and Supervisors (RQF) Highfield Qualifications · Level 3 · covers 2 of 8 standards
Pearson BTEC Level 5 Higher National Diploma in Computing for England Pearson Education Ltd · Level 5 · covers 4 of 8 standards
NCC Education Level 5 Extended Diploma in Computing with Data Science NCC Education Limited · Level 5 · covers 2 of 8 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 BCS Level 4 Diploma - Digital Modular Programme for Data Analysts
Introduction to Data Science and Big Data NCC Education Level 5 Extended Diploma in Computing with 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
Start my Analytics Solutions Consultant plan, free
Your Plan Illustration

Built for Analytics Solutions Consultant

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

  1. Data Analytics Primer NOCN · covers 5 of 8 standards Level 4
  2. Data Analytics Pearson Education Ltd · covers 4 of 8 standards Level 5
  3. Data Analysis BCS, The Chartered Institute for IT · covers 2 of 8 standards Level 4
  4. Introduction to Data Science and Big Data NCC Education Limited · covers 2 of 8 standards Level 5
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as an Analytics Solutions Consultant?

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

How the AI economy is changing work like this

A broad read on this kind of work, not an analysis of this job on its own. Roles that share a pattern get the same answer here.

Fading: AI does more of this

AI is taking over the repetitive data extraction and initial cleaning tasks, freeing you up for more complex analysis.

→
Rising: worth more because of AI

Your ability to interpret and communicate nuanced insights becomes even more critical as AI handles routine data tasks.

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 Analytics Solutions Consultant 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.

Start my Analytics Solutions Consultant plan, free Ready to pay? Subscribe for £70 a month

3What this role really is

We see you

You sometimes wonder if AI will replace your role, but you know that the human touch in interpreting data is irreplaceable. It's a balance of embracing AI tools while ensuring your unique analytical skills shine through.

An Analytics Solutions Consultant takes a business problem and works out how data can answer it. You dig into the numbers to explain what is really going on. You work on specific parts of larger projects, making sure your piece is solid and makes sense.

4A day in the life

Not a job advert. A real day, built from what this role actually holds.

08:45
You kick off your day by diving into SQL, cleaning up data for the customer churn analysis you've been working on.
11:00
Mid-morning, you present a draft of your Tableau dashboard to your Senior Consultant, ready for feedback on clarity and usability.
14:30
After lunch, you conduct a variance analysis in Excel, identifying key trends and anomalies to discuss in tomorrow's stakeholder meeting.
16:00
You wrap up the day documenting your findings in Confluence, ensuring everything is organised for future reference.

5What you'd actually use

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

SQL (PostgreSQL, T-SQL) Intermediate

Writing `SELECT` statements with complex `JOIN`s and `WHERE` clauses to pull exactly the data you need for your analysis from our various databases.

Alteryx Designer / Python (pandas) Intermediate

Using Alteryx to build data transformation workflows, or writing Python scripts with pandas to clean, reshape, and prepare messy datasets for analysis.

Tableau Desktop / Power BI Intermediate

Creating and modifying interactive dashboards and reports from clean data sources. You'll use different chart types and basic calculations to tell a clear story with the data.

Excel (Power Query, VBA) Intermediate

Using PivotTables, VLOOKUPs, and Power Query for quick, ad-hoc analysis, building financial models, or interpreting outputs from other statistical tools.

Jira / Confluence / Miro Intermediate

Managing your personal tasks and updating progress in Jira, contributing to project documentation in Confluence, and participating in (or leading small parts of) brainstorming sessions in Miro.

6What 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 Selection Proposes options to supervisor for review. Decides on methodology for assigned workstreams, consults Senior Consultant on complex or novel approaches. Defines and approves methodologies for entire projects, mentors junior team members on best practices.
Data Source Selection & Extraction Identifies potential data sources, requests access via supervisor. Independently identifies and extracts data from approved sources, flags access issues to manager. Approves data sources for projects, advises on data governance and access strategies.
Report/Dashboard Design Creates basic reports/dashboards from templates under guidance. Designs and builds interactive reports/dashboards for specific workstreams, gets feedback from stakeholders. Sets design standards, reviews and approves complex dashboard architectures.
Project Timeline & Scope Adjustments (for your workstream) Escalates any potential delays or scope changes to supervisor immediately. Proposes minor adjustments to your workstream's timeline or scope to your Senior Consultant, explaining the rationale. Negotiates and approves timeline/scope changes for entire projects with stakeholders.

7How 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.

Task Accuracy
The precision of your data extractions, calculations, and model outputs.
Target · >98% accuracy on data extractions and calculations.

If you're pulling a list of customers for a marketing campaign, we'd expect fewer than 2 errors per 100 records. For a financial calculation, it needs to be spot on, obviously.

Delivery Time
How quickly you turn around ad-hoc data requests and project workstreams.
Target · Ad-hoc data requests completed within 48-hour SLA; project workstreams delivered on agreed timelines (typically within ±10% variance).

A request for 'last quarter's sales by region' should be with the stakeholder in two days. For a report that's part of a bigger project, you'll hit your agreed-upon deadline, give or take a day or two.

Code/Workflow Quality
The readability, maintainability, and error-free execution of your analytical code and data workflows.
Target · Workflows and scripts are well-documented, follow internal coding standards, and run without errors (e.g., <1% error rate on scheduled runs).

Your Alteryx workflow should be easy for another consultant to pick up and understand. Your Python script for data cleaning should have clear comments and not break when new data comes in.

Workstream Completion Rate
The percentage of assigned project workstreams that you take from start to finish, delivering a complete output.
Target · Complete 90% of assigned workstreams end-to-end.

If you're given the task to build the 'customer segmentation model' part of a larger project, you'll deliver a fully working, documented model, not just a partial output.

Stakeholder Communication Clarity
How well you explain complex analytical findings to non-technical business users, making sure they actually understand the 'so what'.
  • Stakeholders confirm understanding in meetings
  • fewer follow-up questions for clarification
  • positive feedback on presentation style
  • ability to simplify complex concepts without losing accuracy.
Problem Deconstruction
Your ability to take a vague business problem and break it down into smaller, testable questions that data can answer.
  • You can articulate the 'ask behind the ask'
  • your analytical plans clearly map to business questions
  • your initial hypotheses are well-formed and logical
  • you ask insightful clarifying questions.
Proactive Issue Identification
How often you spot potential data quality issues, analytical pitfalls, or project risks before they become major problems.
  • You flag data anomalies during initial exploration
  • you raise concerns about a proposed methodology's limitations
  • you suggest alternative approaches when the initial plan hits a snag
  • you anticipate stakeholder pushback.
Informal Mentorship
The extent to which you help newer team members or interns learn the ropes and get unstuck.
  • Junior team members come to you for advice
  • you offer to review their work
  • you share tips and tricks
  • positive feedback from mentees or senior colleagues about your helpfulness.

8Would you like it

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

What people enjoy
Solving Puzzles

You get a real buzz from taking a tangled business question, digging into the data, and figuring out what's really going on. It's like a daily detective challenge.

Spending an afternoon tracking down why two different reports show conflicting numbers for 'active users' and finally finding the subtle difference in their definitions.

Making a Tangible Impact

You want to see your work actually used to make things better. It's not just about producing reports; it's about seeing those reports lead to real changes.

Building a dashboard that helps the Operations team reduce customer waiting times by 10%, and seeing them actively use it every day.

Continuous Learning & Skill Development

You're always keen to pick up new tools, learn different analytical techniques, or understand new parts of the business. The idea of standing still doesn't appeal to you.

Taking the initiative to learn a new Python library to handle a specific data cleaning challenge, even if it's not strictly required for the current project.

What frustrates people
  • The 'Data Janitor' Reality: Spending 80% of your time cleaning and preparing data, and only 20% on the actual analysis.
  • Dashboard Ghost Town: Building a great dashboard only for it to be rarely used because the stakeholder's priorities changed.
  • Fighting for Data Access: The bureaucracy and politics of getting access to data from other departments.
  • Vague, Urgent Requests: Getting asked for 'X by EOD' with no real context or detail.
  • Scope Creep: When the project requirements keep expanding beyond what was initially agreed, making it hard to finish anything.
What this role does not give you
  • A perfectly clean, ready-to-analyse dataset every day.
  • A clear, linear path where every analysis leads directly to a deployed solution.
  • A role where you only interact with other data experts; you'll be talking to all sorts of people.
  • The ability to make strategic business decisions without consulting others; you're advising, not deciding.

9Who you work with

Your work here directly helps our internal teams make better, faster decisions. You're essentially giving them the factual basis to change processes, invest in new areas, or stop doing things that aren't working. Get it right, and you'll see real improvements in efficiency and profitability across the business. Get it wrong, and we might chase the wrong opportunities or miss critical issues.

Inside the business
  • Project Managers (across Operations, Marketing, Finance)
  • Business Unit Leaders (e.g., Head of Sales, Head of Customer Service)
  • Data Engineering Team (for data access and pipelines)
  • Product Owners (when analysing product usage or performance)
  • Finance Business Partners (for cost/revenue analysis)
Outside the business
  • Software Vendors (e.g., Tableau, Alteryx support teams, if troubleshooting)

10What you need before you start

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

  • Proven experience (2-5 years) in an analytical role, ideally within a consulting environment (internal or external), or a similar problem-solving function.
  • Solid grasp of SQL for data extraction and manipulation. You should be able to write complex queries without constant supervision.
  • Demonstrable experience with at least one data visualisation tool (Tableau or Power BI) for building clear, impactful dashboards.
  • Experience with a programming language for data analysis (Python with pandas, or R) or a data transformation tool like Alteryx.
  • A track record of taking a business question, finding the data, analysing it, and presenting clear findings.
  • Strong problem-solving skills – you can break down a complex issue into smaller, manageable parts.

11What to practise next

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

Advanced Data Modelling & Warehousing Concepts

As our data landscape grows, understanding how data is structured and stored becomes critical. You'll need to move beyond just querying data to understanding how it's modelled and how that impacts your analysis. This is about being able to work more effectively with our Data Engineering team.

Star and Snowflake Schemas · ETL/ELT processes · Data Governance principles · Cloud Data Platforms (e.g., Snowflake, Databricks)

  • This quarter: Spend time with our Data Engineering team to understand their current projects and challenges.
  • Next quarter: Take an online course on data warehousing concepts or cloud data platforms.
  • Month 6: Proactively suggest improvements to data models or pipelines based on your analytical needs.
  • Ongoing: Read industry blogs and articles on modern data stack best practices.

Quick win: Ask your Senior Consultant or Lead to walk you through the data lineage for a complex report you're working on. Understand where every piece of data comes from.

Basic Machine Learning & Predictive Analytics

Our internal clients are increasingly asking for more than just descriptive analytics ('what happened?'). They want predictive insights ('what will happen?') and prescriptive advice ('what should we do?'). Having a foundational understanding of ML will help you meet these evolving demands.

Supervised vs. Unsupervised Learning · Common ML Algorithms (e.g., Regression, Classification, Clustering) · Model Evaluation Metrics · Feature Engineering basics

  • This quarter: Complete an introductory online course on machine learning (e.g., Coursera, DataCamp).
  • Next quarter: Try to apply a simple ML model (like linear regression) to a dataset you're already familiar with, perhaps predicting sales or customer churn.
  • Month 6: Discuss with your manager how predictive analytics could add value to one of your current projects.
  • Ongoing: Follow industry leaders and research papers in applied machine learning.

Quick win: Use Python's `scikit-learn` library to run a basic linear regression on a dataset you've already analysed. Compare the predicted values to the actuals. It's a great way to start getting a feel for it.

12Staying current once you are in

What people here do to keep up
  • Regularly engage with online learning platforms (e.g., DataCamp, Coursera, Udemy) to deepen your skills in SQL, Python, and statistical methods.
  • Attend industry webinars or virtual conferences to stay up-to-date on emerging trends in analytics and internal consulting.
  • Participate in internal 'Lunch & Learn' sessions or knowledge-sharing workshops to learn from your colleagues and share your own expertise.
  • Seek out opportunities to shadow senior consultants or architects on projects outside your direct workstream to broaden your understanding of solution design.

13The 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

Frankly, competitors are already using tools like ChatGPT and Claude to draft reports in 10 minutes that used to take us 2 hours. Analysts who figure this out will outproduce their peers by a significant margin. This isn't just about asking questions; it's about crafting the right questions to get the best analytical output.

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

14What you’ll use

What you’ll use

Skills this role draws on

Technical

  • Hypothesis-Driven Problem Solving
  • Stakeholder Requirements Elicitation
  • Solution Architecture & Design (Workstream Level)
  • Business Process Analysis (BPA)

15The 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

    Analytics Solutions Analyst (L1) Promotion

    2-3 years

    Skills to master

    • Independent task execution, basic stakeholder communication, foundational data manipulation and visualisation, understanding of core business processes.

    You're ready to move on when

    • Consistently delivering accurate and timely analytical outputs under supervision.
    • Proactively identifying and solving minor data issues.
    • Starting to ask insightful questions about the 'why' behind the data.
    • Demonstrating a solid grasp of our core analytical tools.
  2. 2

    External Junior Consultant / Data Analyst

    Direct entry (2-5 years experience)

    Skills to master

    • Adapting to our internal systems and processes, understanding our specific business context, building relationships with internal stakeholders, learning our internal consulting methodology.

    You're ready to move on when

    • Proven track record of delivering data-driven insights in a previous role.
    • Strong technical skills in SQL and a BI tool.
    • Ability to quickly understand new business domains.
    • Excellent communication skills for explaining technical concepts to non-technical people.
  3. 3

    Graduate Scheme (with analytics focus)

    3-4 years (including initial L1 period)

    Skills to master

    • All L1 skills, plus taking on more complex individual tasks, starting to manage small project components, and building confidence in direct stakeholder interactions.

    You're ready to move on when

    • Successful completion of a structured graduate programme with analytical rotations.
    • Demonstrated ability to learn new tools and techniques rapidly.
    • Positive feedback from mentors and project leads on initiative and problem-solving.
    • Proactive engagement in learning about the business.

16How people get here · where they go next

Came from
Analytics Solutions Analyst (L1) Promotion
2-3 years
You mastered the art of delivering accurate and timely analytical outputs while starting to ask insightful questions about the data.
You are here
Analytics Solutions Consultant
Mid-Level (2-5 years)
An Analytics Solutions Consultant takes a business problem and works out how data can answer it. You dig into the numbers to explain what is really going on. You work on specific parts of larger projects, making sure your piece is solid and makes sense.
Goes to
Senior Analytics Solutions Consultant (L3)
3-5 years
This role involves leading entire projects, mentoring junior colleagues, and managing client relationships independently.

The long view: This work can lead to designing analytics solutions across whole projects, or managing a team of consultants and architects.

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 Analytics Solutions Consultant is actually changing.

Where it leads

Roles this leads to

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 Analytics Solutions Consultant.

Data Analytics Primer Level 4

Applied to your work in Analytics Solutions Consultant

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.

The Navigator Last time, we discussed the strategic importance of your customer churn analysis. How did your presentation to the stakeholders go?

You It went well, but I think I could improve how I link data insights to business outcomes.

The Navigator Let's focus on crafting a narrative that ties your findings directly to business strategies. For your next task, try framing each insight with a 'so what' that highlights its business relevance.

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 Analytics Solutions Consultant plan, free
A year from now

A year from now, you confidently lead analytical projects, leveraging AI tools to enhance your insights while mentoring others in your team.

See Your Progress Grow Illustration
Analytics Solutions Consultant
  • Hypothesis-Driven Problem Solving
  • Stakeholder Requirements Elicitation
  • Solution Architecture & Design (Workstream Level)
  • Business Process Analysis (BPA)
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.

17The 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

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

  1. Senior Analytics Solutions Consultant (L3)

    3-5 years in current role

    You'll move from owning specific workstreams to leading entire small-to-medium sized projects end-to-end. You'll also start mentoring junior colleagues and managing client relationships more independently.

    • End-to-End Solution Design Architecting complete analytical solutions, not just components.
    • Advanced Business Case Development Building more complex ROI models and benefits realisation plans.
    • Strategic Communication Crafting compelling narratives for senior leadership presentations.
Working with AI on the job

Working with AI

Where AI is starting to help

We're not just talking about the future; we're using AI today to make our Analytics Solutions Consultants more effective and less bogged down in the tedious bits. This isn't about replacing you; it's about giving you superpowers.

Imagine spending less time on the grunt work and more on the actual problem-solving and insight generation. Our internal consulting team is actively integrating AI into our daily workflows, helping you get to the 'aha!' moment faster and deliver more value to our internal clients.

Automated Data Profiling & Cleaning

Use AI tools to automatically scan new datasets for quality issues—think missing values, outliers, or weird inconsistencies. It'll even suggest and generate Python scripts to clean things up, turning hours of manual inspection into minutes of review. You'll still validate, of course, but the heavy lifting is done.

Accelerated Insight Generation

Leverage Natural Language Query (NLQ) features in our BI tools or standalone platforms. You can literally ask complex questions of the data in plain English and get quick answers. This means you can rapidly test hypotheses without writing complex SQL or building new charts from scratch, speeding up your initial exploration phase.

Rapid Project Onboarding

Got a new project? Use an LLM to summarise lengthy project documentation, past analyses, and stakeholder interview transcripts from Confluence. You'll get up to speed on a complex business problem in under an hour, instead of spending days sifting through old files. Think of it as your personal project historian.

Draft-First Communication

Generate first drafts of project charters, weekly stakeholder update emails, and even sections of your final presentation slide decks. The AI handles the boilerplate structure and initial wording, freeing you up to focus on refining the key insights, crafting the narrative, and making sure your recommendations hit home.

Common questions

Common questions

How do you become an Analytics Solutions Consultant?

Common routes in include Analytics Solutions Analyst Promotion (2-3 years), External Junior Consultant / Data Analyst (Direct entry (2-5 years experience)) and Graduate Scheme (with analytics focus) (3-4 years (including initial L1 period)). Times vary with prior experience.

Where can an Analytics Solutions Consultant progress to?

This role can lead on to Senior Analytics Solutions Consultant (3-5 years in current role), depending on the skills you build.

What new skills matter most for an Analytics Solutions Consultant?

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

18Where to go from here

Other roles at Level 3

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

 More jobs in internal consulting

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

The skills built in this role apply across industries, from tech to finance to retail. From here you could move into an analytics role in a specific business unit, into external consulting, or into product management for data products.

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 Analytics Solutions Consultant 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.