United Kingdom · Internal consulting · Senior (5-8 years)

Senior Analytics Solutions Consultant

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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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 bandSenior (5-8 years)
Direct reportsNo direct reports
Reports toManager, Analytics Solutions
UK framework levelUsually a manager, or the deepest specialist in a team

Also advertised as Senior Data Consultant · Lead Analytics Specialist (Internal) · Business Intelligence Lead (Internal Consulting)

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

Pearson BTEC Level 5 Higher National Diploma in Computing for England Pearson Education Ltd · Level 5 · covers 4 of 9 standards

Pearson BTEC Level 5 Higher National Diploma in Digital Technologies Pearson Education Ltd · Level 5 · covers 2 of 9 standards

NOCN Level 4 certificate for Data Analysts NOCN · Level 4 · covers 7 of 9 standards

OTHM Level 7 Diploma in Data Science OTHM Qualifications · Level 7 · covers 5 of 9 standards

Pearson BTEC Level 4 Higher National Certificate in Computing for England Pearson Education Ltd · Level 4 · covers 3 of 9 standards

Highfield Level 3 Diploma for Team Leaders and Supervisors (RQF) Highfield Qualifications · Level 3 · covers 2 of 9 standards

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

The units you would start with

Data Analytics Pearson BTEC Level 5 Higher National Diploma in Computing for England

Data Analytics Primer NOCN Level 4 certificate for Data Analysts

Data Analysis and Visualisation OTHM Level 7 Diploma in Data Science

Data Analysis Highfield Level 3 Diploma for Team Leaders and Supervisors (RQF)

The future skills this job leans on

AI Fluency working with AI as a thinking partner

Data Fluency turning numbers into a decision

AI Governance Fluency using AI responsibly

Systems Fluency seeing the whole picture

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Your Plan Illustration

Built for Senior Analytics Solutions Consultant

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

Data Analytics Pearson Education Ltd · covers 4 of 9 standards Level 5
Data Analytics Primer NOCN · covers 7 of 9 standards Level 4
Data Analysis and Visualisation OTHM Qualifications · covers 5 of 9 standards Level 7
Data Analysis Highfield Qualifications · covers 2 of 9 standards Level 3

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 Analytics Solutions Consultant?

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

The new skills this role is being asked for

Prompt Engineering & LLM Integration
Data Ethics & Responsible AI

Why each one is rising

The future skills this job leans on

AI Fluencyworking with AI as a thinking partner
Data Fluencyturning numbers into a decision
AI Governance Fluencyusing AI responsibly
Systems Fluencyseeing the whole picture

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 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.

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3What this role really is

This job involves leading work on complex business problems using data. You take vague questions from executives and turn them into analytical projects, then design and deliver the answers. You act as a strategic partner to different departments, helping them make better decisions with data. The work covers a wide range of challenges, from operations to customer behaviour. It is hands on, but focused on shaping what gets analysed and how.

4What you'd actually use

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

SQL (PostgreSQL, T-SQL) Advanced

Writing complex queries with CTEs, window functions, and stored procedures to extract, transform, and analyse data from various databases. You'll also be optimising existing queries for performance.

Alteryx Designer / Python (pandas) Expert

Designing and building complex, scalable Alteryx workflows from scratch for data preparation and transformation. Alternatively, writing robust Python scripts with pandas for bespoke data manipulation and feature engineering when Alteryx isn't suitable.

Tableau Desktop / Power BI Advanced

Building complex, interactive dashboards and reports using advanced features like LOD expressions, parameters, and actions. You'll also be managing data sources and optimising dashboard performance for a smooth user experience.

Excel (Power Query, VBA) / Python (scikit-learn, statsmodels) Expert

Building sophisticated financial and operational models in Excel, often using Power Query for data ingestion. For more advanced statistical analysis, you'll be writing Python scripts to run regression, classification, and clustering analyses.

Jira / Confluence / Miro Advanced

Configuring Jira projects and sprints to manage your project portfolio. Owning and structuring the Confluence space for your projects, ensuring clear documentation. Leading complex solution design and brainstorming sessions in Miro with stakeholders.

Snowflake / SAP S/4HANA / Salesforce Intermediate

Writing efficient SQL to extract and join data from these enterprise platforms. You'll need to understand the underlying data structures and the business processes these systems support to get the right data.

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 choice	Coming in	Where you are now	The step above
Project Scope & Approach	Follows defined project plan; escalates any scope changes or technical challenges to supervisor.	Proposes project approach for routine problems; flags potential scope creep to manager; makes minor adjustments to project plan.	Defines project scope and analytical approach for small-to-medium projects; consults with manager on major deviations or resource needs; leads scope definition workshops with stakeholders.
Technical Solution Design	Executes specific tasks within a pre-defined solution architecture; seeks guidance for any technical choices.	Designs components of a larger solution; selects appropriate tools/methods for defined tasks; gets approval for significant design choices.	Designs end-to-end analytical solutions for projects; makes technical architecture decisions (e.g., data flow, model choice, visualisation strategy); ensures solutions are scalable and maintainable.
Stakeholder Communication	Communicates project status to supervisor; responds to direct stakeholder queries with supervision.	Provides regular project updates to immediate stakeholders; manages routine expectations and feedback.	Manages primary stakeholder relationships for projects; presents findings and recommendations to senior leaders; navigates complex stakeholder dynamics and conflicting priorities; 'socialises' sensitive findings.
Mentorship & Team Guidance	Receives guidance and feedback from senior team members.	Provides informal advice or help to new joiners on specific tasks.	Formally mentors 1-2 junior analysts/consultants; conducts code reviews; provides constructive feedback and helps unstick them on complex problems; contributes to team best practices.

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.

Project Delivery Rate

Percentage of analytical projects completed on time and within the agreed scope.

Target · 90% on time, 95% within scope

Delivered 9 out of 10 projects in Q3 on schedule, with the one delay due to an unavoidable external data issue, not internal execution.

Stakeholder Satisfaction (NPS)

Net Promoter Score (NPS) collected from primary project stakeholders after solution delivery.

Target · +50 NPS

Received an average NPS of +65 across your last three major projects, indicating high satisfaction with your collaboration and deliverables.

Solution Adoption Rate

Percentage of target users actively using a new dashboard, report, or analytical tool three months post-launch.

Target · >75% active users

The new Sales Performance dashboard you built showed 80% of the Sales leadership team logging in at least once a week, three months after launch.

Mentorship Impact

Feedback from junior analysts and consultants on your guidance, code reviews, and support.

Target · Average rating of 4.5/5 on structured feedback forms

Two junior team members specifically mentioned your detailed code reviews and patient explanations as crucial to their development in their mid-year reviews.

Proactive Problem Solving

Your ability to anticipate business needs or analytical challenges before they become urgent problems, and propose solutions.

You're bringing ideas to your manager or project sponsors, not just waiting for requests. You've identified potential data quality issues before they impacted a critical report. You're thinking a few steps ahead about what the business will need next.

Quality of Recommendations

The clarity, actionability, and strategic relevance of your analytical insights and proposed business changes.

Your presentations don't just show data
they tell a clear story with a 'so what' and 'now what'. Business leaders are acting on your recommendations. They're coming back to you for advice on new problems, not just data pulls.

Stakeholder Trust & Influence

How well you build and maintain credibility with internal clients, leading to them seeking your input on strategic matters.

You're invited to early-stage planning meetings, not just brought in when they need a report. Stakeholders are openly discussing challenges with you. They're accepting your recommendations even when they're difficult to hear, because they trust your judgment.

Solution Maintainability & Scalability

The technical quality of your analytical solutions, ensuring they're easy to update, robust, and can grow with the business.

Your code is well-commented and follows our standards. Your Alteryx workflows are logically structured. Someone else can pick up your work and understand it quickly. Solutions don't break when underlying data changes slightly.

7Would you like it

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

What people enjoy

Solving Complex Puzzles

You get a buzz from taking a really thorny business problem, deconstructing it, and then using data to reveal the solution. It's the 'aha!' moment when the numbers finally click into place.

Spending a Friday afternoon trying to figure out why customer churn spiked in a specific segment, digging through various data sources until you uncover a correlation with a recent product change.

Making a Tangible Impact

You're not content with just producing reports; you want to see your work actually change things. Knowing that your analysis led to a new strategy or a significant cost saving is what gets you out of bed.

Seeing the Operations team implement a new staffing model based on your demand forecast, and then watching customer wait times drop significantly.

Mentoring and Developing Others

You enjoy sharing your knowledge, guiding junior team members through tough problems, and seeing them grow. You're happy to spend time explaining a complex concept or reviewing someone's code.

Sitting down with a junior analyst to walk them through optimising a SQL query, patiently explaining the 'why' behind each change, and seeing them grasp it.

What frustrates people

The 'Data Janitor' Reality: You'll spend a surprising amount of time (sometimes 70-80%) just finding, cleaning, and prepping data before you can even start the 'fun' analysis.
The 'Report Factory' Perception: Sometimes, business units will treat you like a pair of hands for pulling data, rather than a strategic partner who can help them define the problem.
Dashboard Ghost Town: You'll pour weeks into building a brilliant, insightful dashboard, only to find out later that very few people are actually using it.
Fighting for Data Access: Getting access to the data you need can be a bureaucratic nightmare, with different departments guarding their silos like dragons.
Vague, Urgent Requests: The classic 'I need to understand X by end of day' request, often with little context or detail, landing on your desk just as you've planned your afternoon.
Political Crossfire: Your objective analysis might inadvertently show that one VP's strategy is working and another's isn't, and then you're stuck in the middle managing the fallout.

What this role does not give you

A perfectly predictable, routine workday (expect curveballs regularly).
Guaranteed deployment of every analytical model or solution you build (business priorities shift).
A role where you're solely focused on deep technical research without client interaction.
A quiet, solitary work environment (you'll be collaborating and presenting a lot).

8Who you work with

This role directly drives the quality and adoption of data-driven decision-making across the organisation. You'll be shaping how business units understand their performance, identify opportunities, and mitigate risks. Your work helps us avoid costly mistakes and ensures we're investing in the right areas, ultimately impacting the company's bottom line and strategic direction.

Inside the business

Manager, Analytics Solutions (your direct line)
Project Sponsors (typically VPs or Directors in various business units)
Business Unit Leads (e.g., Head of Marketing, Operations Director)
Junior Analytics Solutions Consultants and Analysts (your mentees)
IT and Data Engineering teams (for data access and infrastructure)

Outside the business

Occasionally, third-party data providers or technology vendors, especially when evaluating new tools or data sources.

9What you need before you start

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

A strong foundation in statistical analysis and quantitative methods. You should be able to interpret model outputs and understand statistical significance.
Proven experience leading analytical projects, even if it was a small workstream, where you were responsible for the end-to-end delivery.
Demonstrable ability to communicate complex technical concepts to non-technical audiences, both verbally and in writing. You can't just talk tech.
Experience mentoring or guiding junior colleagues, perhaps through code reviews, training sessions, or informal support.
A track record of solving real-world business problems using data, not just producing reports.

10What to practise next

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

Advanced Python for Data Science

While you're already an expert, the complexity of our problems will demand even deeper Python skills. We'll be moving beyond basic scripting to building more robust, modular, and production-ready analytical pipelines. This means more focus on software engineering best practices within data science.

Object-Oriented Programming (OOP) in Python · Advanced Data Structures & Algorithms · Testing & Debugging Methodologies · Deployment & Orchestration Frameworks (e.g., Airflow, Prefect) · Cloud-Native Data Services (e.g., AWS Sagemaker, Azure ML)

This week: Refactor a previous Python script using OOP principles.
This month: Explore a new Python library for a specific task (e.g., PySpark for big data, FastAPI for API development).
Month 2: Contribute to an open-source data science project or build a small, well-tested Python package for internal use.
Month 3: Take an advanced Python course focusing on software engineering principles for data scientists.

Quick win: Start writing docstrings and type hints for all your Python functions today. It's a small change with a big impact on code readability and maintainability.

Data Governance & Master Data Management (MDM)

As we rely more heavily on data for critical decisions, the integrity and trustworthiness of that data become paramount. You'll need to understand not just how to use data, but how to ensure it's high quality, consistent, and well-governed across the organisation. This means getting involved earlier in the data lifecycle.

Data Stewardship & Ownership Models · Data Quality Frameworks & Metrics · Metadata Management & Data Catalogues · Data Privacy & Security Best Practices · Data Architecture Principles

This week: Review our internal data governance policies (if they exist) and identify gaps.
This month: Participate in a data quality working group or initiate one for a critical dataset.
Month 2: Research different MDM solutions and their applicability to our organisation.
Month 3: Propose improvements to our data catalogue or metadata management practices.

Quick win: For every new data source you use, proactively document its lineage, known quality issues, and business owner in Confluence. It's a small step towards better data governance.

11Staying current once you are in

What people here do to keep up

Regularly engage with industry thought leaders and communities (e.g., LinkedIn groups, online forums) to stay current on new analytical techniques and tools.
Attend relevant conferences or webinars (e.g., Tableau Conference, PyData) to learn about best practices and network with peers.
Take advanced online courses in areas like machine learning, cloud analytics, or advanced Python programming to deepen your technical skills.
Seek out opportunities to present your work internally or externally, honing your data storytelling and presentation skills.
Actively mentor junior colleagues and participate in internal knowledge-sharing sessions.

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

Competitors are already using Large Language Models (LLMs) to draft reports in minutes that used to take hours. Consultants who master this will outproduce their peers significantly. It's about working smarter, not harder, and leveraging these tools to accelerate every stage of our projects.

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

Data Ethics & Responsible AI

As our analytical solutions become more sophisticated and AI-driven, the ethical implications become more pronounced. We need consultants who can not only build powerful models but also understand and mitigate potential biases, ensure fairness, and uphold privacy. This isn't just a compliance issue; it's about maintaining trust with our customers and employees.

Algorithmic Bias Detection & Mitigation
Fairness Metrics & Explainable AI (XAI)
Data Privacy & Anonymisation Techniques
Ethical Use Cases for AI in Business
Regulatory Landscape for AI (e.g., EU AI Act)

13What you’ll use

What you’ll use

Skills this role draws on

Technical

Hypothesis-Driven Problem Solving
Stakeholder Requirements Elicitation
Solution Architecture & Design
Benefits Realisation & ROI Modelling
Change Management & Adoption Strategy
Business Process Analysis (BPA)

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
From Analytics Solutions Consultant (L2)
2-3 years at L2
Skills to master
- Leading small projects independently, advanced technical proficiency in our core tools, strong stakeholder management for routine requests, and informal mentorship of new joiners.
You're ready to move on when
- Consistently delivering projects on time and to a high standard.
- Being the 'go-to' person for complex technical challenges within your peer group.
- Receiving positive feedback from stakeholders on your communication and problem-solving.
- Proactively identifying new analytical opportunities, not just responding to requests.
2
From Senior Analyst in a Business Unit
5-7 years in a dedicated business unit analytics role
Skills to master
- Adapting to a consulting mindset (problem framing, influencing without authority), broadening your technical stack beyond a single domain, and managing multiple, diverse projects simultaneously.
You're ready to move on when
- You've been the lead analyst on several significant projects within your business unit.
- You're regularly presenting insights to senior leaders in your current role.
- You've built and maintained complex analytical models or dashboards that are critical to your current team.
- You're eager to apply your analytical skills to a wider range of business problems.
3
From External Consulting (Analytics Focus)
3-5 years in a consulting firm (e.g., Big Four, boutique analytics firm)
Skills to master
- Transitioning from client-facing to internal stakeholder management, adapting to internal systems and data nuances, and building long-term internal credibility rather than short-term project wins.
You're ready to move on when
- You've managed client engagements and delivered analytical solutions for external clients.
- You're comfortable with rapid problem framing and solution design under pressure.
- You're looking for a role where you can have a deeper, more sustained impact within one organisation.
- You're keen to apply your structured consulting approach to internal challenges.

15Where this role leads

The long view: This role can lead to director level analytics work, a broader transformation leadership role, or a path towards chief data officer.

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 Analytics Solutions Consultant is actually changing.

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, worked against Senior Analytics Solutions Consultant.

Data Analytics Level 5

Applied to your work in Senior Analytics Solutions Consultant

The objective of this unit is to enable learners to understand and apply data analytics techniques for decision-making. Learners will be able to apply descriptive, predictive, and prescriptive analytic methods, utilising statistical methods, to convert raw data into actionable insights and determine the best course of action.

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.

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

Start my Senior Analytics Solutions Consultant plan, free

See Your Progress Grow Illustration

Senior Analytics Solutions Consultant

Hypothesis-Driven Problem Solving
Stakeholder Requirements Elicitation
Solution Architecture & Design
Benefits Realisation & ROI Modelling
Change Management & Adoption Strategy
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.

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

Lead Analytics Solutions Architect (L4)
3-5 years as Senior Analytics Solutions Consultant

This is a step up into a more technical leadership role, focusing on designing the overall analytical and technical approach for complex, cross-functional projects and potentially managing a small team of architects.
- Enterprise Data Architecture Deeper understanding of data warehousing, data lakes, and cloud-native data platforms.
- Advanced Modelling Techniques Expertise in more complex machine learning models and their deployment.
- Vendor Management & Technology Evaluation Assessing and recommending new tools and platforms for the analytics function.
Manager, Analytics Solutions (L5)
4-6 years as Senior Analytics Solutions Consultant (or Lead Architect)

This path moves you into direct people management, leading a team of consultants and architects. Your focus shifts from individual project delivery to managing a portfolio of projects, talent development, and broader stakeholder relationships.
- Strategic Planning for Analytics Defining the annual objectives and key results for the analytics function.
- Talent Acquisition & Development Recruiting, onboarding, and retaining top analytical talent.
- Cross-Functional Leadership Representing the analytics function in broader organisational initiatives.

Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, a big chunk of consulting work can be repetitive or time-consuming. Imagine if you could cut down on the grunt work and spend more time on the truly strategic, impactful stuff. That's where AI comes in. We're not just talking about buzzwords; we're talking about practical tools that will genuinely make your day-to-day life easier and more productive.

As a Senior Analytics Solutions Consultant, you're constantly juggling data, analysis, stakeholder communication, and project management. AI isn't here to replace you; it's here to be your super-efficient assistant, taking care of the tedious bits so you can focus on the critical thinking, problem-solving, and influencing that only a human can do. Think of it as having an extra pair of hands that never gets tired.

Automated Data Profiling & Cleaning

Use AI tools to automatically scan new datasets for quality issues like missing values, outliers, or inconsistencies. It can even suggest and generate Python scripts to clean and prep your data, turning hours of manual inspection and coding into minutes of review. No more endless VLOOKUPs just to get your data ready.

Accelerated Insight Generation

Leverage Natural Language Query (NLQ) features in our BI tools or standalone LLM platforms. You can literally ask complex questions of your data in plain English and get quick answers, rapidly testing hypotheses without writing complex SQL or building new charts from scratch. It's like having a data expert on speed dial.

Rapid Project Onboarding

Got a new project? Instead of sifting through dozens of lengthy documents, use an LLM to summarise past analyses, stakeholder interview transcripts, and project charters from Confluence. Get yourself (or a new team member) up to speed on a complex business problem in under an hour, rather than days of reading.

Draft-First Communication

Generate first drafts of project charters, weekly stakeholder update emails, or even sections of your final presentation slide decks. The AI handles the boilerplate language and structure, allowing you to focus your brainpower on refining the key insights, crafting the narrative, and ensuring your message lands perfectly. No more staring at a blank page.

Common questions

How do you become a Senior Analytics Solutions Consultant?

Common routes in include From Analytics Solutions Consultant (2-3 years at L2), From Senior Analyst in a Business Unit (5-7 years in a dedicated business unit analytics role) and From External Consulting (Analytics Focus) (3-5 years in a consulting firm (e.g., Big Four, boutique analytics firm)). Times vary with prior experience.

Where can a Senior Analytics Solutions Consultant progress to?

This role can lead on to Lead Analytics Solutions Architect (3-5 years as Senior Analytics Solutions Consultant) and Manager, Analytics Solutions (4-6 years as Senior Analytics Solutions Consultant (or Lead Architect)), depending on the skills you build.

What new skills matter most for a Senior Analytics Solutions Consultant?

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

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 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.

Senior Analytics Solutions Consultant

Where should we send it?

Two short quizzes about you

Will AI change your work as a Senior Analytics Solutions Consultant?

What's rising in its place

Prompt Engineering & LLM Integration

Data Ethics & Responsible AI

Skills this role draws on

Technical

How you actually get there, here

From Analytics Solutions Consultant (L2)

From Senior Analyst in a Business Unit

From External Consulting (Analytics Focus)

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

Roles this leads to

One to one, on the work you already do

Everything else the record holds

The career path, and where it branches

Lead Analytics Solutions Architect (L4)

Manager, Analytics Solutions (L5)

Where AI is starting to help

Automated Data Profiling & Cleaning

Accelerated Insight Generation

Rapid Project Onboarding

Draft-First Communication

Common questions

Want a read on where you stand?