Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Analyst

Sephora
London
11 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

At Sephora we inspire our customers, empower our teams, and help them become the best versions of themselves.  We create an environment where people are valued, and differences are celebrated. Every day, our teams across the world bring to life our purpose: to expand the way the world sees beauty by empowering the ExtraOrdinary in each of us.

We are united by a common goal -to reimagine the future of beauty.


 

The Opportunity

 

Analytics is the compass that guides Sephora on its strategic journey, and we are on the lookout for a Data Analyst who can harness the power of data to propel our business forward. As a Data Analyst, you'll play a critical role in analyzing and interpreting customer data to drive business decisions across our digital platforms. Leveraging your strong experience in BigQuery SQL, you'll craft scripts that seamlessly integrate back-end data with Google Analytics 4 for in-depth customer analysis and segmentation. 

 

Your expertise in data modeling will enable you to map out data structures that support the creation and maintenance of dashboards and reports, tracking key performance indicators (KPIs) related to online engagement, traffic, conversion rates, and marketing effectiveness. In this role, you'll work with data visualization tools like Power BI and Google Data Studio to develop compelling visual reports that convey complex insights in a clear and actionable manner. Additionally, you'll ensure the accuracy and quality of data, while effectively communicating your insights to non-technical stakeholders. 

 

You will also be responsible for: 

  • Writing and optimizing BigQuery SQL scripts for GA4 analysis, integrating back-end data to segment and analyze customer data. 

  • Developing and maintaining dashboards and regular weekly/monthly reports to track KPIs related to performance, online engagement, A/B testing, traffic, conversion rates, marketing attribution, and campaign effectiveness. 

  • Using data visualization tools such as Power BI and Google Data Studio to create clear, actionable insights for stakeholders. 

  • Engaging in data modeling to effectively map out data structures that support business goals. 

  • Utilizing digital analytics tools like Google Analytics and Quantum Metric to deliver data-driven recommendations. 

  • Ensuring the accuracy and quality of data while drawing insightful conclusions and making strategic recommendations. 

 

What You'll Bring  

 

Your passion for detail is matched by your logical thinking and curiosity. You not only obsess over details but also possess the agility to communicate improvements rapidly and clearly. You thrive in an ever-evolving landscape, where driving innovation and continuous improvement is paramount. We are looking for a detail-oriented Data Analyst with strong analytical skills, capable of working both independently and collaboratively within a dynamic team environment. 

We value ambition paired with a logical mindset—individuals who are curious, inquisitive, and able to articulate suggestions with precision. You will utilize your strong foundation in BigQuery SQL, particularly in GA4 analysis, coupled with hands-on experience in data visualization using tools like Power BI. Your deep understanding of digital analytics, especially within Ecommerce and Retail, will enable you to provide actionable insights that drive business success. Your proficiency in digital analytics tools such as Google Analytics and Quantum Metric will be essential in providing recommendations that optimize performance. 

 

Our ideal candidate will also possess: 

  • Proficiency in Google Analytics, Quantum Metric, or similar digital analytics platforms. 

  • Experience with Google Marketing Platform. 

  • Strong communication skills, both written and verbal, for conveying complex data insights to non-technical stakeholders. 

  • An eye for detail and a commitment to data accuracy and quality. 

  • Familiarity with Google Tag Manager, A/B testing tools, competitor research using market share tools, setting up data feed APIs, and UX platforms would be advantageous. 

 

 

While at Sephora, you’ll enjoy...

  • The people.You will be surrounded by some of the most talented leaders and teams – people you can be proud to work with.

  • The learning.We invest in training and developing our teams, and you will continue evolving and building your skills through personalized career plans.

  • The culture.As a leading beauty retailer within the LVMH family, our reach is broad, and our impact is global. It is in our DNA to innovate and, at Sephora, all 40,000 passionate team members across 35 markets and 3,000 stores, are united by a common goal - to reimagine the future of beauty.

You canunleash your creativity,because we’ve got disruptive spirit. You canlearn and evolve,because we empower you to be your best. You canbe yourself,because you are what sets us apart.This,is the future of beauty. Reimagine your future, at Sephora.

Sephora is proud to be an equal opportunity workplace for all. We do not discriminate in recruitment, hiring, training, advancement, or other employment practices. We celebrate diversity and are committed to creating and fostering an inclusive environment for all employees.

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.

Jobs

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Jobs

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Jobs

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.