Raw Material Sampling Analyst

Burberry Limited
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist - Hybrid Work, ML Pipelines & Data Hub

Hybrid Data Scientist: ML & Data Hub

Data Scientist (Sports Analytics)

Data Scientist – Remote UK | Clickstream Modelling

Data Scientist – Remote UK | Clickstream Modelling

Senior RF Data Scientist / Research Engineer

INTRODUCTION

At Burberry, we believe creativity opens spaces. Our purpose is to unlock the power of imagination to push boundaries and open new possibilities for our people, our customers and our communities. This is the core belief that has guided Burberry since it was founded in 1856 and is central to how we operate as a company today.

We aim to provide an environment for creative minds from different backgrounds to thrive, bringing a wide range of skills and experiences to everything we do. As a purposeful, values-driven brand, we are committed to being a force for good in the world as well, creating the next generation of sustainable luxury for customers, driving industry change and championing our communities. 

JOB PURPOSE

This role drives data-informed decisions to optimise sampling procurement and supply chain processes. Combining expertise in data analysis, app development, and task automation, you will enhance the RMP Sampling team’s efficiency in managing raw materials. With a focus on optimising procurement data and inventory management, you will streamline workflows, improve coordination, and implement systems that elevate supply chain performance.
 

RESPONSIBILITIES
  • Conduct data entry and analysis on raw material procurement, including costs, lead times, and supplier metrics, using tools like Power BI and Excel.
  • Create dashboards and reports to track KPIs such as spend, inventory levels, and supplier performance, delivering actionable insights.
  • Analyse material availability, risks, and forecasts to enhance procurement stability and supply chain efficiency.
  • Streamline processes and develop workflow solutions using Microsoft Power Apps and Power Automate to improve supply chain coordination.
  • Monitor supplier and warehouse performance, optimise inventory at third-party warehouses, and support strategies for improved sourcing and logistics.
  • Ensure procurement data accuracy, integrate systems, and drive continuous process improvements for efficiency and cost-effectiveness.
     
PERSONAL PROFILE
  • Bachelor’s Degree in Data Science, Supply Chain Management, Business, or a related field.
  • 2-4 years of data analysis experience, ideally in luxury fashion, with strong proficiency in Excel, Power BI, and Tableau.
  • Expertise in Microsoft Power Apps and Power Automate to streamline workflows, optimise processes, and enhance collaboration.
  • Knowledge of PLM software and third-party warehouse automation systems.
  • Strong analytical skills, attention to detail, and ability to work cross-functionally with flexibility and initiative.
  • Familiarity with the luxury fashion industry, including raw materials, sustainability trends, and emerging technologies.
MEASURES OF SUCCESS
FOOTER

Burberry is an Equal Opportunities Employer and as such, treats all applications equally and recruits purely on the basis of skills and experience.

 

Posting Notes: United Kingdom || Not Applicable || London || SC CENTRAL OPERATIONS || RAW MATERIALS MANAGEMENT -RTW || n/a ||

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.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.