UK

United Kingdom · Marketing · C-Suite (20+ years)

VP of Marketing Science & Technology

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 bandC-Suite (20+ years)
  • Reports toChief Executive Officer (CEO)
  • UK framework levelUsually a director, accountable for a division and its numbers

Also advertised as Chief Marketing Data Officer · Global Head of Marketing Analytics · Executive Director of Marketing Intelligence

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

OTHM Level 7 Diploma in Data Science OTHM Qualifications · Level 7 · covers 5 of 9 standards
NCC Education Level 5 Extended Diploma in Computing with Data Science NCC Education Limited · Level 5 · covers 4 of 9 standards
Pearson BTEC Level 5 Higher National Diploma in Computing for England Pearson Education Ltd · Level 5 · covers 3 of 9 standards
Pearson BTEC Level 5 Higher National Diploma in Digital Technologies Pearson Education Ltd · Level 5 · covers 2 of 9 standards
Pearson BTEC Level 5 Higher National Diploma in Business Pearson Education Ltd · Level 5 · covers 1 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 Science Foundations OTHM Level 7 Diploma in Data Science
Introduction to Data Science and Big Data NCC Education Level 5 Extended Diploma in Computing with Data Science
Data Analytics Pearson BTEC Level 5 Higher National Diploma in Computing for England
Advanced Data Analytics for Productivity NOCN Level 5 Certificate in Strategic Organisational Productivity Management
Business Data Analytics and Insights Pearson BTEC Level 5 Higher National Diploma in Business

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
Frontier Fluency the next wave, beyond mainstream AI
Change Fluency taking people through change
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Your Plan Illustration

Built for VP of Marketing Science & Technology

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

  1. Data Science Foundations OTHM Qualifications · covers 5 of 9 standards Level 7
  2. Introduction to Data Science and Big Data NCC Education Limited · covers 4 of 9 standards Level 5
  3. Data Analytics Pearson Education Ltd · covers 3 of 9 standards Level 5
  4. Advanced Data Analytics for Productivity NOCN · covers 1 of 9 standards Level 5
  5. Business Data Analytics and Insights Pearson Education Ltd · covers 1 of 9 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 a VP of Marketing Science & Technology?

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

  • AI Governance & Ethical Frameworks
  • Decentralised Data Ecosystems & Data Clean Rooms
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 VP of Marketing Science & Technology 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 role sets the long-term vision for how data and technology shape a marketing organisation's strategy and decisions.

4What you'd actually use

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

Python (pandas, scikit-learn, statsmodels, PyMC) Strategic

Setting coding standards, evaluating new frameworks, understanding the trade-offs between different modelling approaches for business goals. You won't be writing code daily, but you'll understand its strategic implications and guide your teams.

SQL (PostgreSQL, BigQuery, Snowflake) Architect

Making strategic decisions on data warehousing platforms (e.g., Snowflake vs. BigQuery), designing the overall marketing data model and schema, and ensuring data integrity and accessibility across the enterprise.

BI & Visualization (Tableau, Looker) Strategic

Governing the entire BI ecosystem, defining enterprise-wide KPIs and dashboarding standards, and presenting high-level insights from these tools to the C-suite and Board. You'll ensure consistent, actionable reporting.

Customer Data Platform (CDP) (Segment, Tealium) Strategic

Leading the selection, implementation, and strategic evolution of our CDP. Defining the enterprise-wide customer data and event taxonomy to ensure a unified customer view and effective audience activation.

Cloud ML Platforms (AWS SageMaker, GCP Vertex AI) Architect

Designing the cloud infrastructure for the entire marketing data science function, managing budgets for cloud spend, and overseeing vendor relationships for platform services. You'll ensure scalability and cost-efficiency.

Financial Planning (Anaplan, Pigment) Advanced

Partnering with the CFO and Finance leadership to model complex marketing budget scenarios, forecast ROI for major initiatives, and use these platforms to justify significant investments and report on P&L impact to the Board.

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
Marketing Data Strategy & Vision N/A N/A N/A
Budget Allocation & P&L Management N/A N/A N/A
Organisational Design & Talent N/A N/A N/A
Major MarTech & Data Infrastructure Investments N/A N/A N/A
External Representation & Partnerships N/A N/A N/A

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.

Marketing-Attributed Incremental Revenue
The net new revenue directly attributable to marketing data science initiatives and optimised spend.
Target · Achieve >£10M in incremental profit annually from data-driven marketing decisions.

In Q2, data science-led optimisation of media spend resulted in an additional £3.5M in revenue, exceeding the £2.5M target for the quarter.

LTV:CAC Ratio Improvement
The year-on-year improvement in the ratio of Customer Lifetime Value to Customer Acquisition Cost, reflecting marketing efficiency.
Target · Increase the LTV:CAC ratio by >15% annually through strategic data science interventions.

By optimising acquisition channels and retention programmes based on CLV models, the LTV:CAC ratio improved from 3.0:1 to 3.6:1 over the last fiscal year.

Marketing Budget Optimisation & ROI
The efficiency and effectiveness of marketing spend, ensuring maximum return on investment across all channels.
Target · Influence the allocation of >£100M in marketing spend, demonstrating a minimum 15% improvement in overall marketing ROI.

Through advanced MMM, you'll shift £15M of budget from underperforming channels to high-impact ones, resulting in an additional £20M in revenue.

Data Maturity Score
Our internal assessment of the sophistication and impact of our marketing data capabilities, from basic reporting to predictive and prescriptive analytics.
Target · Elevate the marketing data maturity score from 'Strategic' to 'Optimising' within two years.

Successfully implemented a unified customer data platform and advanced experimentation framework, moving our score from 4.2 to 4.7 on a 5-point scale.

Board and Executive Trust
The level of confidence the Board and C-suite have in the marketing data science function's insights and strategic recommendations.
  • Regular invitations to Board meetings for strategic input
  • executive decisions frequently referencing data science insights
  • proactive consultation on major business initiatives
  • positive feedback from CEO/Board members on presentations and strategic guidance.
Organisational Impact & Influence
The extent to which marketing data science drives strategic shifts and innovation across the wider business.
  • Data science insights leading to new product development or market entry
  • successful adoption of new martech stacks across the organisation
  • internal teams actively seeking collaboration and data-driven solutions
  • recognition as an internal thought leader on data and customer behaviour.
Talent Development & Retention
The ability to attract, develop, and retain top-tier marketing data science talent.
  • High retention rates within the team
  • successful internal promotions and career progression
  • positive feedback in employee engagement surveys
  • ability to recruit senior talent in a competitive market
  • fostering a culture of continuous learning and innovation.
Industry Thought Leadership
Our external reputation and influence within the marketing data science community.
  • Speaking engagements at major industry conferences
  • publications in reputable journals or industry blogs
  • active participation in industry working groups
  • positive media mentions or analyst recognition for our data science capabilities.

7Would you like it

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

What people enjoy
Shaping Enterprise Strategy

You'll spend your days in strategic planning sessions, advising the CEO on market opportunities, and presenting to the Board on the future of marketing. You'll love seeing your long-term vision for data science become a core part of the company's overall business strategy.

Leading the quarterly strategic offsite where the entire executive team aligns on the next 12-18 months of marketing investment, directly informed by your team's insights.

Significant P&L Impact

The thought of data science initiatives driving £10M+ in incremental revenue or saving millions in inefficient spend genuinely excites you. You'll be constantly looking for ways to maximise the commercial return on every data science investment.

Successfully championing a multi-million pound investment in a new CDP, knowing it will unlock significant LTV growth and reduce CAC across the business.

Building High-Performing Teams & Capabilities

You'll get immense satisfaction from recruiting top-tier talent, mentoring your Directors, and seeing your team's capabilities grow. Building a world-class marketing data science function from the ground up (or taking an existing one to the next level) is a huge driver for you.

Developing a comprehensive career framework for your team that sees junior analysts progress to senior leadership roles, fostering a strong talent pipeline.

What frustrates people
  • The 'HiPPO' (Highest Paid Person's Opinion) overriding data-driven insights, despite overwhelming evidence.
  • Slow organisational adoption of new data science capabilities or technologies due to internal resistance or bureaucracy.
  • Constant shifts in executive priorities that derail long-term strategic roadmaps and require frequent re-prioritisation.
  • The challenge of securing significant budget and resources for foundational data infrastructure that doesn't show immediate ROI.
  • Navigating complex data privacy regulations (e.g., GDPR, CCPA) that constantly impact data collection and usage strategies.
  • The difficulty in recruiting and retaining truly exceptional data science talent in a highly competitive market.
What this role does not give you
  • Daily hands-on coding or model building – your role is strategic oversight and architectural design.
  • A purely technical individual contributor path – this is a leadership role with significant people and programme management.
  • A quiet, predictable environment – expect constant change, high pressure, and complex stakeholder negotiations.
  • The luxury of avoiding difficult conversations or political challenges – you'll be at the forefront of these.

8Who you work with

This role directly impacts the top and bottom lines of the business. You'll be responsible for ensuring our marketing investments are highly efficient and effective, driving customer acquisition, retention, and lifetime value. Your strategic decisions will influence product roadmaps, market entry strategies, and our overall competitive positioning. Ultimately, you're building the data-driven engine that powers our entire marketing organisation's success, influencing multi-year business strategies and P&L outcomes of £10M+.

Inside the business
  • CEO and Executive Leadership Team
  • Chief Commercial Officer (CCO)
  • Chief Technology Officer (CTO)
  • Chief Financial Officer (CFO)
  • Heads of Product, Sales, and Operations
  • Board of Directors
Outside the business
  • Investors and Analysts
  • Key Marketing Technology Vendors and Partners
  • Industry Regulators and Compliance Bodies
  • External Consultants and Advisors

9What you need before you start

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

  • Proven track record of leading and scaling a large (25+ people) data science or analytics function within a complex, global organisation.
  • Direct experience managing a significant P&L (minimum £10M+) and demonstrating clear ROI from data science initiatives.
  • Extensive experience presenting to and influencing C-suite executives and Board members on strategic data and technology initiatives.
  • Deep expertise in architecting and implementing enterprise-level marketing technology (MarTech) stacks and data infrastructure.
  • A minimum of 20 years' progressive experience in data science, analytics, or related quantitative fields, with at least 5-7 years at a Director/VP level.
  • Demonstrated ability to drive organisational change and embed a data-driven culture across a large enterprise.

10What to practise next

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

Quantum Computing for Marketing Optimisation

While still nascent, quantum computing holds the potential to solve optimisation problems currently intractable for classical computers. As a strategic leader, you'll need to understand its potential future impact on complex marketing challenges like media mix optimisation, hyper-personalisation, and supply chain logistics.

Quantum Annealing & Gate-Based Quantum Computing · Quantum Machine Learning Algorithms · Optimisation Problems in Quantum Context · Hybrid Quantum-Classical Algorithms · Quantum Supremacy & Error Correction

  • This quarter: Read introductory materials on quantum computing for business leaders (e.g., IBM Quantum Experience tutorials).
  • Next 6 months: Attend a webinar or virtual conference on quantum computing applications in business or finance.
  • Next 12 months: Identify one or two 'moonshot' marketing optimisation problems that might be solved by quantum computing in the distant future.
  • Ongoing: Foster a small internal R&D group to track quantum advancements and explore potential use cases.

Quick win: Subscribe to leading quantum computing newsletters (e.g., The Quantum Daily) to stay informed on the latest breakthroughs without deep technical dives.

Advanced Neuromarketing & Behavioural Science Integration

Moving beyond traditional survey data, integrating insights from neuroscience and behavioural economics offers a deeper understanding of customer decision-making. As a leader, you'll explore how to ethically incorporate these insights to build more persuasive and effective marketing strategies.

Cognitive Biases & Heuristics · Emotional Data Analysis · Choice Architecture & Nudging · Ethical Implications of Persuasive Technology · Experimental Design for Behavioural Interventions

  • This quarter: Read foundational books on behavioural economics (e.g., 'Nudge', 'Thinking, Fast and Slow').
  • Next 6 months: Partner with a university research group or specialist consultancy in behavioural science to explore potential applications.
  • Next 12 months: Pilot a small-scale behavioural marketing experiment, focusing on ethical design and clear consent.
  • Ongoing: Integrate behavioural science principles into your team's experimentation framework and hypothesis generation.

Quick win: Run a workshop with your leadership team on common cognitive biases and how they might impact marketing effectiveness. It's a fun way to start the conversation.

11Staying current once you are in

What people here do to keep up
  • Regularly engage with industry thought leaders and academic researchers in data science, AI, and marketing through conferences, webinars, and direct networking.
  • Actively participate in executive peer groups or leadership forums to share best practices and challenges.
  • Mentor emerging leaders within and outside your organisation, fostering a culture of knowledge sharing.
  • Contribute to industry publications or speak at major conferences, establishing yourself and the company as a leader in marketing science.
  • Dedicate time to continuous learning on emerging technologies (e.g., quantum computing, Web3 data models) and regulatory landscapes.

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.

AI Governance & Ethical Frameworks

With the rapid advancement and adoption of AI, particularly generative AI, regulatory bodies and consumers are demanding greater transparency, fairness, and accountability. As a leader, you'll be responsible for defining and enforcing the ethical guardrails for all AI applications in marketing.

  • Algorithmic Bias Detection & Mitigation
  • AI Explainability (XAI)
  • Data Lineage & Provenance for AI
  • Privacy-Preserving AI Techniques
  • Regulatory Compliance for AI

Decentralised Data Ecosystems & Data Clean Rooms

The deprecation of third-party cookies and increasing privacy concerns are driving a shift towards more secure, privacy-preserving methods of data collaboration. Understanding and strategising around decentralised data architectures and data clean rooms will be critical for future cross-company analytics and activation.

  • Data Clean Room Architectures
  • Differential Privacy & K-anonymity
  • Zero-Knowledge Proofs in Data Sharing
  • Web3 & Blockchain for Data Provenance
  • Identity Resolution in Privacy-First World

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • Enterprise Marketing Mix Modelling (MMM)
  • Advanced Causal Inference & Experimentation Design
  • Marketing Technology (MarTech) Architecture
  • Customer Data Strategy & Governance
  • Ethical AI in Marketing

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

    Director of Marketing Data Science (Large Enterprise)

    3-5 years at Director level

    Skills to master

    • Mastering large-team leadership, managing multi-million pound budgets, driving cross-functional strategic alignment, and consistently delivering significant business impact from data science programmes.

    You're ready to move on when

    • Successfully led a team of 15+ data scientists and analysts, with demonstrable talent development.
    • Consistently delivered 10%+ ROI on marketing data science investments.
    • Regularly presented to and influenced C-suite executives on strategic initiatives.
    • Architected and overseen the implementation of major marketing data platforms.
  2. 2

    Chief Data Officer (Mid-size/Growth Company)

    3-4 years as CDO

    Skills to master

    • Broader data governance across the entire enterprise, managing diverse data functions (e.g., BI, data engineering, data science), and establishing a company-wide data strategy.

    You're ready to move on when

    • Demonstrated ability to build a comprehensive data strategy from the ground up.
    • Managed a diverse data organisation beyond just marketing.
    • Successfully navigated company-wide data privacy and compliance challenges.
    • Proven track record of driving data literacy and adoption across an organisation.
  3. 3

    VP of Analytics/Data Science (Other Functions)

    4-6 years as VP

    Skills to master

    • Applying data science leadership principles to different business domains (e.g., Product, Sales, Operations), adapting to new data sets and business problems, and building credibility in a new functional area.

    You're ready to move on when

    • Successfully transitioned leadership skills to a new domain, demonstrating rapid learning and impact.
    • Built and led high-performing data teams in multiple functional areas.
    • Proven ability to translate business problems into data science solutions across varied contexts.

15Where this role leads

The long view: This work can lead towards senior leadership roles such as Chief Executive Officer or Chief Commercial 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 VP of Marketing Science & Technology is actually changing.

Where it leads

Roles this leads to

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

  • Chief Executive Officer (CEO) / Managing Director

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 Science Foundations, worked against VP of Marketing Science & Technology.

Data Science Foundations Level 7

Applied to your work in VP of Marketing Science & Technology

1. To enable the learner to define the scope and landscape of Data Science and differentiate the roles of Data Scientists from other IT professionals. 2. To enable the learner to evaluate key topics within Data Science, including data administration, governance, and big data sources. 3. To enable the learner to describe the architecture and core elements of Apache Hadoop. 4. To enable the learner to analyse the advantages and disadvantages of utilising Artificial Intelligence techniques in a business context. 5. To enable the learner to critically analyse the impact of Big Data on digital transformation within organisations and its effects on users. 6. To enable the learner to review strategies for ensuring data compliance and explain the responsibilities and challenges faced by data specialists.

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.

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See Your Progress Grow Illustration
VP of Marketing Science & Technology
  • Enterprise Marketing Mix Modelling (MMM)
  • Advanced Causal Inference & Experimentation Design
  • Marketing Technology (MarTech) Architecture
  • Customer Data Strategy & Governance
  • Ethical AI in Marketing
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

VP of Marketing Science & Technology is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. Chief Commercial Officer (CCO)

    3-5 years

    Direct P&L ownership for all revenue-generating functions (Sales, Marketing, Business Development).

    • Go-to-market strategy for new products and markets.
    • Strategic pricing and revenue management.
    • Global market expansion and competitive strategy.
    • Building and managing large, diverse commercial teams.

  2. Chief Executive Officer (CEO) / Managing Director

    5-10 years

    Ultimate accountability for the entire company's strategy, operations, and financial performance.

    • Operations and supply chain management.
    • Product innovation and portfolio strategy.
    • Legal and regulatory compliance at an enterprise level.
    • Building and leading a cohesive executive team.
Working with AI on the job

Working with AI

Where AI is starting to help

As a VP, your time is precious, and every decision carries significant weight. Imagine having an intelligent co-pilot that helps you sift through vast amounts of information, validate strategic hypotheses, and communicate complex ideas with unparalleled clarity. That's what AI can do for you.

AI isn't just for junior analysts anymore. For executive leaders, it's a powerful tool for strategic decision support, market intelligence, and streamlining high-level communications. We're talking about using AI to elevate your strategic thinking, not replace it. It's about making you more effective at the highest level.

Strategic Scenario Planning

Use AI to rapidly model complex market shifts, competitive responses, and potential regulatory changes. Feed in various inputs and get probabilistic outcomes for different strategic choices, helping you make more informed, data-backed decisions for multi-year plans.

Board & Investor Comms

Draft compelling board papers, investor presentations, and executive summaries in minutes. AI can help refine your messaging, anticipate tough questions from analysts, and even generate concise answers, ensuring you're always prepared and articulate.

Innovation Scouting

Leverage AI to continuously scan global research, startup landscapes, and patent databases to identify emerging marketing technologies, data science methodologies, and competitive threats. Get concise summaries of what matters, helping you stay ahead of the curve.

Organisational Design & Talent Strategy

Use AI to analyse skill gaps within your team, model optimal team structures for new strategic initiatives, and even help draft job descriptions for critical hires. It's about optimising your human capital for maximum impact.

Common questions

Common questions

How do you become a VP of Marketing Science & Technology?

Common routes in include Director of Marketing Data Science (Large Enterprise) (3-5 years at Director level), Chief Data Officer (Mid-size/Growth Company) (3-4 years as CDO) and VP of Analytics/Data Science (Other Functions) (4-6 years as VP). Times vary with prior experience.

Where can a VP of Marketing Science & Technology progress to?

This role can lead on to Chief Commercial Officer (CCO) (3-5 years) and Chief Executive Officer (CEO) / Managing Director (5-10 years), depending on the skills you build.

What new skills matter most for a VP of Marketing Science & Technology?

Increasingly, AI Governance & Ethical Frameworks and Decentralised Data Ecosystems & Data Clean Rooms. 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.

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17Where to go from here

Other roles at Level 7

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

 More jobs in marketing

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

Skills in data-driven strategy, technology architecture and executive leadership carry across sectors. This can include e-commerce, financial services, healthcare, media and technology companies. Leaders who can use data and AI for strategic advantage are needed across many industries.

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 VP of Marketing Science & Technology 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.