National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Digital Commerce Data Analyst

Ralph Lauren Corporation
London
2 weeks ago
Create job alert

Ralph Lauren Corporation (NYSE:RL) is a global leader in the design, marketing and distribution of premium lifestyle products in five categories: apparel, accessories, home, fragrances, and hospitality. For more than 50 years, Ralph Lauren's reputation and distinctive image have been consistently developed across an expanding number of products, brands and international markets. The Company's brand names, which include Ralph Lauren, Ralph Lauren Collection, Ralph Lauren Purple Label, Polo Ralph Lauren, Double RL, Lauren Ralph Lauren, Polo Ralph Lauren Children, Chaps, among others, constitute one of the world's most widely recognized families of consumer brands.

At Ralph Lauren, we unite and inspire the communities within our company as well as those in which we serve by amplifying voices and perspectives to create a culture of belonging, ensuring inclusion, and fairness for all. We foster a culture of inclusion through: Talent, Education & Communication, Employee Groups and Celebration.

Position Overview

Key role in the EMEA E-commerce planning & analytics team ensuring they will deliver insights, reporting, and advanced analytics to drive business decisions and support optimizing the digital customer journey, customer services, and performance marketing. They will solve complex business problems / challenges through data analytics and will story-tell the actionable insights to the key stakeholders to drive and encourage data-driven decision making. They will build key relationships with internal and external stakeholders, RLE associates and other analysts around the business. They will become an SME for one of the Digital Commerce Teams i.e. Performance Marketing, and will own and maintain that dialogue whilst also pro-actively delivering innovative and creative analytics in that space.

• Develop a reporting suite that clearly and accurately demonstrate ROI and profitability, from campaigns, collections, customer journeys, digital product, and merchandise product perspective using Adobe, Dataiku, Microstrategy tools, across a range of metrics that cover all stages of the consumer journey, transactions and voice of the customer interactions.

• Creation and maintenance of reports and dashboards using web analytics data and data visualisation tools, with the ambition to automate all reporting across the business, whilst monitoring the core KPIs vs. targets.

• Proactively seek to solve complex business problems/challenges through data analytics and will translate data into actionable insights and drive data-driven decision making.

• Play a key role in the experimentation process and UX improvements through A/B & MVT tests

• Monitor competitors’ activities and provide updates on best cases and market trends.

• Become the E-commerce team's analytics power user, promoting tool awareness and capability (adobe/microstrategy/Dataiku)

• Monitor competitors’ activities and provide updates on best cases and market trends.

• Liaise with appointed external agencies who are supporting digital analytics.

Experience, Skills & Knowledge

  • SQL
  • Dataiku (nice to have)
  • Microstrategy (nice to have)
  • Tableau (nice to have)
  • Knowledge of the ecommerce analytics landscape


#J-18808-Ljbffr

Related Jobs

View all jobs

Digital Commerce Data Analyst

Digital Commerce Data Analyst

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Manager, AI Data Quality

National AI Awards 2025

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.

Data Science Jobs Skills Radar 2026: Emerging Tools, Languages & Platforms to Learn Now

The UK’s data science job market is evolving fast—from forecasting models and AI assistants to real-time decision systems. In 2026, data scientists aren’t just expected to build models—they’re responsible for shaping insights that fuel everything from patient care to predictive banking. Welcome to the Data Science Jobs Skills Radar 2026—your essential annual guide to the languages, tools, and platforms driving demand across the UK. Whether you’re entering the job market or reskilling mid-career, this roadmap helps you prioritise the skills that matter most right now.

How to Find Hidden Data Science Jobs in the UK Using Professional Bodies like the RSS, BCS & More

The data science job market in the UK is thriving—but also increasingly competitive. As organisations in finance, healthcare, retail, government, and tech accelerate digital transformation, the demand for data talent has soared. Yet many of the best data science jobs are never posted publicly. They’re shared behind closed doors—within professional networks, at invite-only events, or through member-only mailing lists and specialist interest groups. These “hidden” roles are often filled through referrals, collaborations, or direct outreach to trusted experts. In this guide, we’ll show you how to unlock these hidden opportunities by engaging with key UK professional bodies such as the Royal Statistical Society (RSS), BCS (The Chartered Institute for IT), and Turing Society, plus communities like PyData and AI UK. You’ll learn how to use directories, CPD events, and networks to move beyond job boards—and into roles where you’re approached, not just applying.

How to Get a Better Data Science Job After a Lay-Off or Redundancy

Redundancy can be tough to face, especially in a competitive field like data science. But it’s important to know: your experience, analytical thinking, and modelling skills are still in demand. Across sectors like healthcare, finance, e-commerce, government and AI startups, UK employers continue to seek data scientists who can deliver value through insight, prediction, and automation. This guide will walk you through how to bounce back from redundancy with purpose and clarity—whether you're a data analyst looking to step up, a mid-level data scientist, or a machine learning specialist seeking a better-aligned opportunity.