Business & Data Insight Analyst Brands at M&S

  • Marks & Spencer
  • Paddington Station, Praed Street, London, UK
  • 01/05/2021
Full time Data Science Data Analytics Big Data Data Management Statistics

Job Description

Marks and Spencer’s are looking for data driven people with a passion for the industry & a curiosity for the market. As a Business & Data Insight Analyst, you will be responsible for providing insight and analysis to support the shaping and delivery of the New Business Development strategy for Clothing and Home. This is an exciting role & a chance to influence through data the right categories & brands Marks & Spencer’s partners with.


  • Asks stakeholders analytical question and uses excellent problem solving skills to present potential options and solutions
  • Helps decision-makers, by presenting data in an accessible, informative way.
  • Understands the key business drivers for M&S and how they relate to the overarching business strategy
  • Continually scans market to identify opportunities for acquisition or partnership, conducting research to ensure fit with M&S
  • Collects, organises and manipulates large amounts of data using databases and other technologies.
  • Presents and re-structure data tailored to required output
  • Builds data models and uses insight to make recommendations


  • Can tell a story through data
  • Thinks creatively about problems and is able to support decision makers’ business-related questions using the data sets available
  • Excellent problem solver
  • Demonstrable passion and interest in consumer sectors - exposure to retail and other consumer-facing sectors desirable
  • Experience in problem analysis, intellectually curious and able to generate ideas to solve business problems
  • Able to communicate effectively, build relationships across the business and work collaboratively to attain results that meet the business needs
  • Experience in multiple data visualisation tools e.g. Power BI, Spotfire, Tableau
  • Proficient in fundamental statistics and data science concepts (regression, clustering, classification, etc.).