Marketing Data Analyst

Nicholson Glover
London
10 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

HR Data Analyst

Business Data Analyst

Business Data Analyst

Data Analyst - Sales Operations

Data Analyst

Location:West London (Hybrid)

Industry:Retail

Function:CRM Analytics | Loyalty Programmes | Marketing Insight

Contract Type:Permanent


✨ The Opportunity

Are you passionate about turning CRM and loyalty data into actionable insight that improves customer experiences? A major UK organisation, globally recognised in its sector, is looking for aCRM & Loyalty Data Analystto join its growing marketing data team.

This is a unique opportunity to shape customer strategy in a high-impact environment, using data to optimise marketing communications, loyalty engagement, and customer lifetime value.


🔍 What You’ll Be Doing

  • Analyse CRM and loyalty programme data to uncover insights that improve targeting, retention, and customer value.
  • Work with internal and agency teams to report on performance of customer marketing and loyalty campaigns.
  • Develop regular and ad-hoc reports focused on segmentation, customer journeys, and campaign KPIs.
  • Collaborate with performance marketing, brand, and data platform teams to ensure consistency and integration across data sources.
  • Provide recommendations that directly influence marketing personalisation and campaign optimisation strategies.
  • Contribute to a more self-service analytics approach by improving data processes and dashboard efficiency.

✅ What We’re Looking For

  • 3–6 years of experiencein a data analytics role, with a focus onCRM or loyalty marketing.
  • Deep understanding of CRM systems, customer data, and lifecycle marketing metrics.
  • Strong data storytelling skills, with the ability to present complex insights clearly to marketing and commercial stakeholders.
  • Experience managing and integrating data from multiple platforms (e.g., CRM, email, loyalty apps, social).
  • Exposure to campaign performance reporting, customer segmentation, and A/B testing.
  • Desirable:experience withPython or Rfor marketing analytics or performance optimisation. Salesforce, Power BI, Tableau for Data Visualisation.


Bonus if you have experience with tools like Salesforce, Power BI, Tableau, or other customer analytics platforms—though these are not required.

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.

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

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.