Want to get hired at Ralph Lauren?

Analytics Analyst

Ralph Lauren

Nutley, NJOn Site

Original Job Summary

Overview

Ralph Lauren Corporation is a global leader in premium lifestyle products including apparel, accessories, home, fragrances, and hospitality. With over 50 years of reputation, the company consistently develops its brand names and expands internationally. This Analytics Analyst role is based in the New York metro area and supports DTC business teams and IT partners by enhancing analytic capabilities and ensuring data quality and consistency.

Key Responsibilities

  • Collaborate with DTC business teams to document and enhance analytics use cases.
  • Create impactful dashboards and reports using BI tools like Tableau and Power BI.
  • Ensure data quality and consistency across reporting platforms.
  • Communicate insights through effective data visualizations for actionable business decisions.
  • Partner with IT to troubleshoot issues, execute enhancements, and drive tool adoption.
  • Promote effective data reporting practices and educate business teams.

Technical Knowledge and Communication

Experience with MicroStrategy, Dataiku, Excel, SQL, Python, and Agile methods is valued. Familiarity with JIRA, Alteryx, and collaborative project tools is a plus. The role requires balancing detailed analytics with big-picture strategic thinking.

Education & Experience

Candidates with retail, ecommerce, or related analytical/business intelligence experience are preferred. Direct experience in retail metrics, omnichannel analytics, and cross-functional teamwork is advantageous.

Key skills/competency

  • Analytics
  • Business Intelligence
  • Data Visualization
  • DTC
  • Dashboard
  • SQL
  • Python
  • Agile
  • Retail
  • Collaboration

How to Get Hired at Ralph Lauren

🎯 Tips for Getting Hired

  • Customize your resume: Align skills with Ralph Lauren’s analytics needs.
  • Highlight BI expertise: Emphasize Tableau, Power BI and SQL skills.
  • Leverage industry experience: Detail retail and ecommerce work.
  • Prepare for behavioral questions: Share examples of data-driven decision making.

📝 Interview Preparation Advice

Technical Preparation

Practice SQL queries and data manipulation.
Review BI tools like Tableau and Power BI.
Brush up on Python scripting for data analysis.
Study Agile techniques and data visualization methods.

Behavioral Questions

Describe teamwork in data projects.
Explain a challenging analytics problem.
Discuss handling multiple project priorities.
Share examples of cross-functional collaboration.