Merchandising Analytics Manager

Our Opportunity:

Chewy is looking for an Autoship Analytics Manager to join our Merchandising Analytics Team. As the Manager of Autoship Analytics, you will be at the forefront of shaping and optimizing our Autoship program through data-driven insights. If you have a passion for unraveling the complexities of subscription-based models and possess a consistent record in analytics, we invite you to join our innovative team. The ideal candidate will have a strong analytical background, a deep understanding of data-driven decision-making, and a passion for getting results in a fast-paced environment. In this role, you will own regular reporting, delivering key insights and recommendation communication with the team member population. You will also be partnering with Team Members to create programmatic analytical deep dives to understand the drivers of sign-ups, cancelations, retentions etc. Outputs from these efforts would inform where we have selection gaps, up/cross sell opportunities and risks involved. This role will also examine the intersection between promotion strategy and the Autoship program to understand promotional efficacy based on success metrics of Autoship signups and retention. Additionally, you will partner with the Data Science team to build models to optimize Autoship important metrics. The person in this role will work cross-functionally with category management, product, finance and other analytics teams throughout the organization to create complementary solutions which help data tell the story that is required to understand both the inputs and outputs of our business.

What you'll do:

• Dive deep into Autoship program data, analyzing drivers of subscription-specific metrics such as sign ups, cancellations, customer churn/retention, customer lifetime value, and subscription adoption patterns, and understand the impact promotions have on these metrics
• Identify areas of opportunities in assortment selection, up/cross sell and quantify them
• Own regular reporting of the trends and patterns in the business and communicate with cross functional teams and senior leadership along with development of scalable dashboard in partnership with BI Team
• Extract actionable insights to drive strategic decisions for the continuous improvement of the Autoship program
• Partner closely with Enterprise Data Engineers to enhance existing data tables, develop new data tables and implement rigorous data governance practices, with a keen eye on the intricacies of subscription program data
• Apply advanced statistical methods and predictive modeling techniques to forecast Autoship program growth, subscription renewal/churn rates in partnership with Data Science Team
• Provide timely and accurate insights to support proactive decision-making in the evolving landscape of Autoship program
• Work closely with Category Management, Finance, Marketing, Operations, and Product teams to align on the key challenges of the Autoship program, identify primary goals of the program and the analytical needs in specific
• Provide analytical support for the development and enhancement of subscription-specific features, ensuring harmony across the Autoship ecosystem

What you'll need:

• Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Mathematics, Economics, or related field) or equivalent experience
• 5+ years of validated experience in analyzing data and sharing key insights (preferably in retail space)
• Previous experience analyzing subscription-based businesses/projects is a plus
• 3+ years of experience with BI/visualization tools like Tableau, Power BI, BO, etc.
• 3+ years of experience with data modeling in large Data warehousing, data lake environment
• 1+ years of data science experience with building regression, classification models (preferred)
• Advanced analytical skills with excellent knowledge of SQL
• Excellent oral and written communication skills including the ability to communicate effectively with both technical and non-technical collaborators
• Ability to travel up to 10% of the time