Master Data Analyst

Charlotte Tilbury Beauty
City of London
4 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst - E-Commerce

Data Analyst Training Course (Excel, SQL & Power BI)

Data Engineer (18 Months FTC)

Data Analyst

About Charlotte Tilbury Beauty

Founded by British makeup artist and beauty entrepreneur Charlotte Tilbury MBE in 2013, Charlotte Tilbury Beauty has revolutionised the face of the global beauty industry by decoding makeup applications for everyone, everywhere with an easy‑to‑use, easy‑to‑choose, easy‑to‑gift range. Today, Charlotte Tilbury Beauty continues to break records across countries, channels and categories and to scale at pace. Over the last 10 years, the brand has experienced exceptional growth and is one of the most talked‑about brands in the beauty industry and beyond. It has become a global sensation across 50 markets (and growing) with over 2,300 employees worldwide who are part of the dream team. Today, the company is a truly global business delivering market‑leading growth, innovative retail and product launches fuelled by industry‑leading tech, all with an internal culture of embracing challenges, disruptive thinking, winning together and sharing the magic. The energy behind the brand is infectious, and as we grow we are always looking for extraordinary talent who want to contribute to our success and help drive our limitless ambitions.


12 Month Fixed‑Term Contract (FTC)


About the Role

The Product Master Data Analyst enables the interactions between Supply Chain, Finance, Systems, NPD, Regulatory, eCommerce and suppliers by ensuring consistent data management for product, financial and inventory information. You will play a key role in the creation and management of data that facilitates a range of processes supporting our data customers both inside and outside the business.


Responsibilities

  • Create, maintain, and update product master data in PDM and in the ERP system
  • Ensure product attributes (SKU code, UPC and EANs, BOMs, pricing, units of measure, categories, regulatory attributes) are accurate, complete and consistent
  • Partner with stakeholders to gather requirements for new product setups and changes
  • Develop and enforce data governance rules, standards and processes to maintain data quality
  • Conduct regular data audits, identify discrepancies and resolve data integrity issues
  • Perform root‑cause analysis on issues raised and work to resolve, prevent and design those issues out of our processes
  • Support ERP system enhancements, data migration projects and testing activities related to product data
  • Provide reporting and analytics on master data KPIs, including completeness, accuracy and timeliness
  • Collaborate with the Business Systems Team to troubleshoot master data issues
  • Train end‑users and support data‑related change management initiatives
  • Facilitate the downstream flow of product data to other teams and systems, understanding the impact of changes in master data on these downstream processes
  • Document and maintain operational procedures and processes

Qualifications

  • Bachelor's degree in business, Supply Chain, Information Systems or a related field
  • Extensive experience in master data management, preferably with a focus on product data
  • Hands‑on experience with at least one major ERP system (SAP, Oracle or similar)
  • Strong understanding of product lifecycle, supply‑chain processes and data dependencies in ERP
  • Proficiency in Excel and data analysis tools
  • Knowledge of data governance principles and best practices
  • Excellent attention to detail, problem‑solving and communication skills
  • Ability to manage multiple priorities and collaborate across global, cross‑functional teams
  • Ability to thrive in a changing environment as we implement our new master data strategy

Why Join Us?

  • Be part of a values‑driven, high‑growth journey with an ultimate vision to empower everyone, everywhere to be the best version of themselves
  • Hybrid working model with flexibility, allowing you to work how best suits you
  • 25 days holiday plus bank holidays and an additional day to celebrate your birthday
  • Inclusive parental leave policy supporting all parents and carers throughout their parenting and caring journey
  • Financial security and planning with our pension and life assurance for all
  • Wellness and social benefits including Medicash, Employee Assist Programs and regular social connects with colleagues
  • Bring your furry friend to work on our allocated dog‑friendly days and spaces
  • Generous product discount and gifting!

At Charlotte Tilbury Beauty, our mission is to empower everybody in the world to be the most beautiful version of themselves. We celebrate and support diversity and encourage hiring people with diverse backgrounds, cultures, voices, beliefs and perspectives into our growing global workforce. By doing so, we better serve our communities, customers, employees and the candidates that take part in our recruitment process.


#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 Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.