Data Analytics Manager- Individual Contributor

Chewy is seeking a Senior Merchandising Data Analytics Manager to join our dynamic Merchandising Analytics team in FLL, Boston, or Seattle, leading the Selection C Vendor Analytics function.

In this high-impact Individual Contributor role, you’ll shape the analytical foundation driving Chewy’s product selection growth, vendor insights, and category expansion strategies. You’ll partner with senior leadership to influence business decisions, develop scalable data solutions, and translate insights into actions that enhance customer experience and vendor performance.

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:

• Lead Selection Analytics:
• Develop frameworks to evaluate Chewy’s assortment coverage, identify white-space opportunities, and measure SKU productivity, new item ramp- up, and lifecycle performance across categories.
• Deliver clear, actionable insights in written (e.g., white papers, presentations) and verbal form to influence decision-making at the highest levels
• Vendor Insights Performance:
• Build comprehensive vendor health reports and analytical models that evaluate vendor performance
• Partnership Strategy:
• Collaborate with Category Managers, Finance and other cross functional teams to inform joint business planning and negotiation strategies using data-driven insights during Annual Vendor Negotiations
• Analytical Roadmap Tooling:
• Partner with Data Science, Engineering, and Product teams to build scalable data products and dashboards (e.g., Selection Gap Tools, Selection Growth Trackers, Vendor Health reporting etc., selection growth trackers).
• They will also lead initiatives leveraging Generative AI to build intelligent selection agents that automate insights and enhance merchandising decision-making.
• Team Leadership s Collaboration: Serve as a senior analytics lead, mentoring other analysts and elevating analytical rigor across the Partner cross- functionally with Marketing, Supply Chain, and Pricing Analytics to align on category trends, product availability, and promotional performance, ensuring consistent and high-quality insights across stakeholders.

• Bachelor’s degree in a quantitative or business field (e.g., Finance, Supply Chain, Economics, Math, or related discipline).
• 6+ years of experience leading large-scale analytics projects/programs, preferably in retail or ecommerce
• Experience leveraging Generative AI tools or frameworks to develop analytical or decision-support solutions, such as selection or insights agents
• Strong SQL expertise, with the ability to build datasets and perform complex queries across multiple systems.
• Experience in applying advanced analytics techniques, such as predictive modeling to forecast sales trends, clustering to segment customers, or regression analysis to understand drivers of performance.
• Proficiency in statistical tools and programming languages like R or Python to develop and automate advanced models.
• Strong written and verbal communication skills, including experience presenting to senior leadership and writing formal reports or white papers.
• Demonstrated leadership experience, including managing analysts or data engineers and influencing cross-functional teams.
• Familiarity with ecommerce and retail metrics, including pricing, inventory, assortment, and financial KPIs.
• Proficiency in data visualization tools (e.g., Tableau) and advanced Excel
• Track record of operating effectively in ambiguous environments, driving clarity, and achieving, * Advanced degree (e.g., Master’s in Analytics, Business, or related field).
• Hands-on experience with R, Python, or similar programming
• Project Management Certification or experience leading large cross-functional
• Background in data modeling and building scalable analytics