Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior CRM Data Analyst

Wunderman Thompson
City of London
1 week ago
Create job alert

Who We Are:
At VML, we are a beacon of innovation and growth in an ever-evolving world. Our heritage is built upon a century of combined expertise, where creativity meets technology, and diverse perspectives ignite inspiration. With the merger of VMLY&R and Wunderman Thompson, we have forged a new path as a growth partner that is part creative agency, part consultancy, and part technology powerhouse.

Our global family now encompasses over 30,000 employees across 150+ offices in 64 markets, each contributing to a culture that values connection, belonging, and the power of differences. Our expertise spans the entire customer journey, offering deep insights in communications, commerce, consultancy, CRM, CX, data, production, and technology. We deliver end-to-end solutions that result in revolutionary work.

We are looking for a Senior CRM Analyst to work within the VML Data team. The Senior Analyst will analyse data to deliver value through understanding our clients’ customers and the performance of marketing activities.

Working closely with the wider analytics and data team you will be responsible for the development and delivery of measurement and insight projects across various marketing activities and contribute to answering business questions, ultimately ensuring that we are making best use of available data to deliver against the client vision.

On a day-to-day basis you will take ownership and leadership of analysis projects, delivering them to a high degree of accuracy and take a role in presenting results and insights to clients.

This is predominantly a technical role grounded in customer data, so you should be experienced in handling large customer data sets. Communication and interpersonal skills are important, both in collaborating with clients and colleagues across multiple disciplines.

Role & Responsibilities
  • Design, manage, and deliver end-to-end analyses aimed at helping Marketing to improve the experience of the customer
  • Deliver measurement and effectiveness projects, including dashboard reporting and deep dive evaluations to understand the impact marketing has on customer behaviour
  • Deliver and take lead on customer projects (segmentation, modelling), utilising statistical techniques to develop a deep understanding of customers
  • Ensure that the most relevant methodologies are applied to measure and evaluate, proactively recommending better ways of working
  • Develop and provide written and verbal output on reports and presentations, supporting with recommendations on marketing strategy
  • Manage and resolve data issues involving quality and consistency of data
  • Be the clients trusted advisor on data and analytical methodology - make it easy for them to make business decisions based on data
  • Present to clients and attend client meetings.
  • Be highly collaborative in integrating data work into agency deliverables, working with strategy and account teams to develop a culture of data informed decision-making.
  • Offer leadership and expertise to support the development of junior team members
  • Develop the skills and knowledge of colleagues, creating and sustaining a learning culture within the team.
Skills and experience
  • 3+ years working in a marketing or related field as an analyst or senior analyst
  • Experience of coding languages for analysis (Python & SQL preferred)
  • Experience of platforms such as Salesforce
  • Experience of developing wrireframes and creating dashboards
  • High level Microsoft Word, Excel and PPT skills
  • Proven record of delivering high quality outputs
  • Attention to detail and a commitment to accuracy
  • Ability to manage own workload autonomously and thrive in an agency environment
  • Well-developed numeracy skills
  • Able to translate business needs and requirements to analytical methods and outputs
  • Good written and verbal communication skills
  • High level analytical skills in relation to performance analysis
  • Experience of devising, implementing and managing reporting dashboard design, update and automation using tools such as PowerBI, Tableau and Looker Studio
  • Good knowledge of advanced data analysis techniques that include customer segmentation, predictive modelling, multivariate analysis, querying and reporting tools, A/B testing and statistical significance

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office an average of four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.

WPP (VML) is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

VML is a WPP Agency. For more information, please visit our website, and follow VML on our social channels via Instagram, LinkedIn and X.

We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior CRM Data Analyst

Marketing Data Analyst

Senior Marketing Data Analyst (FTC for 3 months)

Senior Marketing Data Analyst (FTC for 3 months)

Senior Data Analyst

Senior Data Analyst

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.