Senior Data Analytics Manager

Our Opportunity:

Chewy is seeking a Senior Data Analytics Manager to join our dynamic Retail Analytics team in Bellevue, WA, supporting Chewy+, Chewy’s membership program. In this high-impact Individual Contributor role, you will lead analytics strategy and insights to drive member acquisition, engagement, retention, and long-term customer value. You will partner closely with Product, Marketing, Finance, and Technology teams to ensure Chewy+ decisions are grounded in rigorous, data-driven insights.

The ideal candidate combines analytical depth with strong business acumen—able to navigate ambiguity, uncover opportunities, and deliver clear, data-driven narratives. This role requires a hands-on leader who can design robust datasets, lead complex analyses, and turn insights into measurable outcomes that fuel Chewy’s growth.

What You’ll Do:

• Develop and own analytical frameworks to measure Chewy+ member acquisition, activation, engagement, retention, churn, and lifetime value.
• Define and track core Chewy+ KPIs, including cohort performance, incremental value, cannibalization, and ROI.
• Lead deep-dive analyses on member behavior, purchase frequency, basket composition, and cross-category lift.
• Design and evaluate A/B tests and quasi-experiments to inform Chewy+ pricing, benefits, and promotional strategies.
• Partner with Data Science to develop models that assess the incrementality of the product.
• Ensure consistent metric definitions, data quality, and governance across Chewy+ reporting.
• Collaborate with Finance on Chewy+ P&L, unit economics, and long-term value modeling.
• Work closely with Data Engineering and BI teams to enable reliable, well-modeled loyalty datasets.

What You’ll Need:

• Bachelor’s degree in Analytics, Statistics, Economics, Mathematics, Computer Science, or a related field (Master’s preferred).
• 6+ years of experience in analytics, business intelligence, or data science, preferably in e-commerce, subscription, or loyalty programs.
• Advanced SQL skills and experience working with large, complex datasets.
• Strong experience with Python or R and data visualization tools such as Tableau or Power BI.
• Experience with customer lifecycle metrics, cohort analysis, and CLV modeling.
• Strong analytical thinking with the ability to translate insights into clear business recommendations.
• Excellent communication skills and ability to influence senior stakeholders.
• Ability to thrive in ambiguous environments and structure open-ended problems.