Senior Analyst, Data Strategy

Ralph Lauren
London
9 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Performance and Data Analyst (SEND)

Housing Needs Research and Data Analyst

Data Analyst

HR System and Data Analyst - Maternity Cover

HR System and Data Analyst - Maternity Cover

Company Description
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
We are seeking a passionate and highly motivated Senior Data Strategy Analyst to join the EMEA Data Strategy team. The Data Strategy team is the driver of end-to-end data and technology capabilities to enable first in class customer centric marketing. Reporting into the Senior Data Strategy Manager, the successful candidate will be responsible for discovering insights from large data sets and support data driven decisions to deliver better product, service and relevance to consumers.

Essential Duties & Responsibilities

  • Develop a comprehensive understanding of our data landscape, customer journeys, marketing experiences, and predictive model usage across our Marketing and Clienteling activities
  • Lead analysis of our BAU Marketing and Clienteling experience to help our CIX team make effective optimisations
  • Own deep dive analyses across our Marketing and Clienteling experiences, and present complex insights through creative storytelling to the CIX team
  • Lead CRM test design and post campaign analyses to clearly communicate learning and recommendations to senior stakeholders
  • Present analyses to senior leadership team as well as large audiences in a clear and concise manner
  • Use understanding of our existing predive models to make optimisations to our customer experiences across the EMEA region and to develop the models for better customer engagement, retention and sales
  • Build visualisation to highlight clear trends and correlations in BI tools like Tableau
  • Collaborate with internal and external stakeholders to drive data-led business decisions

    Experience, Skills & Knowledge

  • Relevant data experience in Data Strategy, CRM or Data Science or relevant educational qualifications (eg: Mathematics, Engineering, Statistics, Marketing)
  • Experience of collation, interpretation, and analysis of multiple sources of data (SQL databases, APIs, web scraping) and data types
  • Highly numerate & analytical with strong communication skills
  • Experience in manipulating data through advanced quantitative methods: data models, statistics, machine learning
  • Experience in presenting insights to non-technical stakeholders
  • Excellent planning and organizing skills with a drive for results, problem solving and action oriented
  • Team player with great interpersonal and communication skills (both verbal and written)
  • Quick learner, with a taste for discovering new technical tools and spotting data inconsistencies
    #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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.