Our Opportunity:

We are looking for a Merchandising Analytics Manager at our Boston, MA location to dive deep into promotions data, examining the factors influencing promotion-specific metrics such as promotion redemptions, new customer acquisition and reactivation, customer churn/retention, customer lifetime value, and promotion redemption patterns.

What You’ll Do: 

• Identify areas of opportunities in promotion optimization and performance enhancement.
• Own regular reporting of business trends and patterns in the business and communicate with cross functional teams and senior leadership along with development of scalable dashboards in partnership with BI Team.
• Extract actionable insights to drive strategic decisions for the continuous improvement of the overall promotion program.
• Partner closely with enterprise data engineers to enhance existing data tables, develop new data tables and implement rigorous data governance practices.
• Partner with business analysts and data engineering teams to prioritize, QA, and release new data tables, metrics, and analytics solutions.
• Utilize advanced statistical methods and predictive modeling techniques to forecast promotion program growth and incremental revenue in partnership with data science team.
• Provide timely and accurate insights to support proactive decision-making in the evolving landscape of promotions.
• Work closely with category management, finance, marketing, operations, and product teams to align on key challenges of the promotion program, identify primary goals of the program and analytical needs.
• Provide analytical support for the development and enhancement of promotion strategies, ensuring synergy across the Chewy ecosystem.
• 10% domestic travel required.
• Telecommuting permitted.

What You’ll Need:

• Bachelor’s degree in Statistics, Economics, or a related field and 5 years of experience.
• Will accept Master’s and 3 years of experience.
• Experience must include 3 years in: advanced analytical skills and sharing key insights on promotional efficacy and customer behavior;
• SQL, advanced Excel (data connections, VBA, etc.), BI/visualization tools like Access, Tableau, Power BI, and executing complex data analysis;
• Python R;
• Data modeling in large data warehousing, data lake environment;
• Supply chain, inventory management, project management, data analysis & modeling, and trend forecasting;
• Proficiency in interpreting business metrics, executing complex analysis, and connecting multiple data sources to explain business performance;
• Understanding of Financial KPIs and P&L statement; and
• Managing cross-functional projects.
• Experience must include 2 years with writing analytical & technical papers.
• 10% domestic travel required.
• Telecommuting permitted.
• The position is eligible for the Employee Referral Program.