Work Placement / Internship

Product Industrial Placement 2022

Product Design/Data Science/Analytics.

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Want to build yourself a legacy you’ll always be proud of? Our most innovative training programme yet is your chance to do just that. Intentionally designed to help you shape the fast-moving world of retail and e-commerce, it’s a masterclass in practical product training, structured mentorship, and 360-feedback.   

Spanning 12 months, you’ll rotate around our business and different product teams learning new skills and gaining new experiences. It’s all about giving you exposure to a variety of projects and the talented people driving them – so you come to realise that there’s infinite ways to progress your career in M&S. If you’re ready to become an M&S Legend of Tomorrow, it’s time to begin.   

Take your place in our Digital & Data team and you’ll find everything you need to kick off your career in Product and begin shaping the world of retail – your way. From access to in-house development programmes,  working closely with seasoned product managers, designers, developers, data scientists and subject matter experts on variety of  problem spaces and product areas, to external product courses that’ll help you become an expert in your field, this is a springboard on to big things.   

Working in Product 

You’ll join a squad focused on delivering the best customer experiences across Personalisation, Banking, Apps, Web and Sparks. Acting as the voice of the customer, you’ll leverage insight to identify, test and optimise a variety of possible features and solutions to best reinforce the M&S value proposition and turbocharge Digital at M&S. 

What skills will you develop? 

  • You’ll learn how to frame and lead discovery, defining the problem space and hypotheses around how to solve for your user problem 
  • You’ll collaborate with the team in validation, building analytical skills in feasibility, usability, determining value and business viability. 
  • You’ll build a product mindset as you work to establish OKRs and build a product strategy to deliver results.  
  • You’ll learn how define and deliver a product and gain experience in the tasks involved: how to move from Discovery through to a prioritised roadmap; how to document requirements and facilitate delivery; how to analyse performance of and then optimise a product 
  • We’ll build on your communication skills so that you’ll be able to engage and influence stakeholders at all levels within the company 

What We Look For

If you’re all about finding ways to be innovative, ethical, and sustainable, you’ve already got the makings of an M&S Legend of Tomorrow. What you need now is the launchpad to bring your ideas to life. That’s what you’ll find right here. We’re always looking for curious, analytical, adaptable, and proactive students who care about what comes next – as passionate about reimagining retail for good, as they are about carving out their own career.


  • A keen and demonstrable interest in product, data, technology and retail, either via relevant qualifications, experience or self-directed learning.  
  • A self-starter who identifies opportunity, is passionate about solving problems, encourages new ideas and brings people together to drive improvements and change. 
  • Strong written and verbal communication skills, and an ability to build relationships 
  • Curious and analytical, with a user-centric approach and a mindset of continuous improvement. 
  • A collaborative team player: listens actively and is able to analyse and consolidate multiple opinions and insight to optimise value delivery. 

Nice to have  

  • Experience or knowledge of retail, product management, product design, data and analytics.


  • 28 days' holiday
  • Holiday buy
  • Bonus 
  • Pension
  • Cycle to work

Become an M&S Legend of Tomorrow. Apply today.   

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Job ID Number: 19853
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Opportunity Overview

  • Today
  • Multiple vacancies
  • Competitive salary + benefits
  • All grades
  • 1 Year
  • London
    (Show map)

Preferred Disciplines...

  • Analytics
  • Computer Science
  • Data Science
  • Information Technology
  • Maths
  • Statistics

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