Ref#: W176753
Department: Data Analytics
City: Bangalore
State/Province: Karnataka
Location: India
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
The Product Manager– Data Products supports the execution and success of Ralph Lauren’s enterprise Data Product strategy by providing analytical rigor, insights, and operational support to Data Product Managers. Working closely with Product Managers and cross-functional teams, this role helps ensure data products are clearly understood, well-measured, adopted by users, and continuously improved.
As Ralph Lauren advances its multi-year digital and AI-driven transformation—spanning predictive buying, demand forecasting, personalization, and omnichannel experiences—the Product Analyst plays a key role in translating business needs and product intent into metrics, insights, and actionable analysis. The role acts as a bridge between business stakeholders, product managers, data engineering, analytics, and governance teams.
The Product Analyst is hands-on, detail-oriented, and comfortable managing relationships across functions, while operating within the strategic direction set by Product Managers and the Head of Data Products.
1. Product Analytics & Performance Tracking
- Support Data Product Managers by defining and maintaining KPIs, success metrics, and performance dashboards for data products.
- Track adoption, usage, availability, and quality metrics and highlight trends or issues.
- Conduct analyses to assess whether data products are meeting expected business outcomes.
- Prepare clear summaries and insights for product reviews, roadmap discussions, and stakeholder updates.
2. Business & Stakeholder Support
- Work with Product Managers to engage business stakeholders and understand their data and decision-making needs.
- Help translate business questions into structured analytical requirements.
- Support stakeholder communications by providing data-backed insights, usage findings, and impact assessments.
- Build strong working relationships through responsiveness, clarity, and reliability.
3. Value Measurement & Insights
- Assist Product Managers in tracking value realization metrics such as efficiency gains, decision support, or process improvements.
- Maintain baseline and post-launch measurements to support benefit tracking.
- Identify early signals of low adoption, misalignment, or data quality issues and escalate appropriately.
- Contribute analytical input to prioritization and iteration discussions.
4. Product Lifecycle Support
- Support the data product lifecycle from discovery through launch and ongoing iteration.
- Help ensure analytical readiness for launches, including tracking plans and success criteria.
- Collaborate with data engineering and analytics teams to validate metric definitions and outputs.
- Document learnings, insights, and feedback to inform continuous improvement.
5. Data Quality, Governance & Trust
- Partner with governance and engineering teams to help monitor data quality, consistency, and reliability.
- Validate that metrics and insights are interpretable and aligned with agreed definitions.
- Surface risks related to metric interpretation, data gaps, or inconsistencies.
- Support responsible data usage by improving transparency and understanding of data products.
Experience, Skills, and Knowledge
Required
- 4–7+ years of experience in product analytics, data analytics, business analytics, or related roles.
- Experience working with enterprise data, analytics platforms, or data products.
- Strong analytical skills with the ability to interpret data and communicate insights clearly.
- Experience collaborating with product managers, business stakeholders, and technical teams.
- Solid understanding of data engineering, BI, and analytics concepts.
Preferred
- Experience in retail, consumer goods, or digital commerce environments.
- Familiarity with Agile or product-based delivery models.
- Comfort working in global, matrixed organizations.
- Exposure to cloud-based data platforms.
