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.

The specific salary offered to a candidate may be influenced by a variety of factors including but not limited to the candidate's relevant experience, education, and work location. In addition, this position is eligible for 401k and a new hire and annual equity grant.
We offer different types of insurance and benefits, such as medical/Rx, vision, dental, life, disability, hospital indemnity, critical illness, and accident. We offer parental leave, family services benefits, backup dependent care, flexible spending accounts, telemedicine, pet adoption reimbursement, employee assistance program, and many discounts including 10% off pet insurance and 20% off at Chewy.com.
Exempt salary team members have unlimited PTO, subject to manager approval. Team members will receive six paid holidays per year. Team members may be eligible for paid sick and family leave in compliance with applicable state and local regulations.
Base Salary Range
$129,500-$207,000 USD
Chewy is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, gender, citizenship, marital status, religion, age, disability, gender identity, results of genetic testing, veteran status, as well as any other legally-protected characteristic. If you have a disability under the Americans with Disabilities Act or similar law, and you need an accommodation during the application process or to perform these job requirements, or if you need a religious accommodation, please contact [email protected].
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