Senior Data Analyst - Customer Analytics

Just Eat Takeaway.com
City of London
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Ready for a challenge?

Just Eat Takeaway.com is a leading global online food delivery platform. Our vision is to empower everyday convenience. Whether it’s a Friday-night feast, a post-work meal, or groceries, our tech platform connects tens of millions of customers with hundreds of thousands of restaurant, grocery and convenience partners across the globe.


About this role

As a Senior Customer Analyst in our UK Analytics team, you will play a pivotal role in understanding and shaping the customer experience across our business. You’ll lead the charge on analysing customer behaviour, lifecycle journeys, loyalty program performance, and customer base dynamics—delivering insights that influence strategic decisions and help us build lasting relationships with our customers.


This is not just a numbers role – it’s about using data to uncover what drives our customers, creating compelling stories, and enabling the business to act decisively in a competitive, fast-changing environment.


This is a hands-on technical role where you\'ll own and deliver end-to-end analyses, build smart customer segmentation, track key lifecycle and loyalty KPIs, and continuously improve how we understand and engage our customer base. Working closely with key stakeholders across Marketing, CRM, Product, and Data, you’ll be at the core of our mission to put customers at the heart of every decision.


These are some of the key ingredients to the role:

  • Customer Base Management: Analyse performance of segmentation frameworks and base management strategies to improve retention, drive reactivation, and support lifecycle marketing initiatives.
  • Loyalty Program Analytics: Measure the effectiveness and ROI of loyalty initiatives, track enrolment and engagement trends, and identify optimisation opportunities.
  • Insights Delivery: Provide actionable insights into customer trends, preferences, and churn risks to shape CRM and marketing strategies.
  • Performance Monitoring: Build and maintain dashboards and reporting tools to monitor key customer KPIs such as retention, LTV, churn, and engagement.
  • Stakeholder Collaboration: Partner with local and global teams across CRM, Marketing, and Product to ensure insights are embedded in decision-making.
  • Visual Storytelling: Use tools like Tableau, Looker, or Sheets to turn data into clear, impactful stories that drive action.
  • Continuous Improvement: Identify opportunities to refine our understanding of customer behaviour through advanced analytics, experimentation, and testing.

What will you bring to the table?

  • Experience in customer or lifecycle analytics, ideally within a B2C, subscription, or loyalty-driven business.
  • Proven expertise in analysing customer journeys and behavioural data to drive strategic decisions.
  • Experience with loyalty or membership program analytics and customer segmentation.
  • Strong SQL skills (mandatory - there will be a live assessment!), with experience in Python or R being a plus.
  • Skilled in data visualisation tools such as Tableau or Looker.
  • Ability to present findings clearly to stakeholders, including non-technical audiences.
  • Strong understanding of key customer metrics (e.g. retention, LTV, churn) and performance drivers.
  • Evidence of delivering insights that have directly improved customer engagement, retention, or commercial outcomes.
  • Comfortable working across cross-functional teams and influencing senior stakeholders.

Inclusion, Diversity & Belonging

No matter who you are, what you look like, who you love, or where you are from, you can find your place at Just Eat Takeaway.com. We’re committed to creating an inclusive culture, encouraging diversity of people and thinking, in which all employees feel they truly belong and can bring their most colourful selves to work every day.


What else are we delivering?

Want to know more about our JETers, culture or company? Have a look at our career site where you can find people\'s stories, blogs, podcasts and more JET morsels.


Are you ready to take your seat? Apply now!


#J-18808-Ljbffr

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.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.