Analytics Manager – Supplier Inventory Optimization
| Company | Wayfair |
|---|---|
| Location | Boston, MA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Senior |
Requirements
- Bachelor’s degree in Business, Supply Chain/Operations, or Engineering discipline
- 5+ years of analytical experience in operations, retail, engineering, consulting, strategy or finance
- Advanced experience with Microsoft Excel or Google Sheets, SQL or GBQ, and data visualization tools such as Google Data Studio (Looker, Tableau, or PowerBI)
- Experience working in a program/project management setting with high attention to detail and proven ability to manage multiple, competing priorities simultaneously
- Solid technical understanding of how tech stack (various architectures/frameworks, databases, cloud / data infrastructure, microservices, code repositories, prod/dev environments, etc.) work in enterprise and commercial software
- Strong written and verbal communication skill with a focus on stakeholder management experience
Responsibilities
- Collaborate cross functionally on a global scale with product, engineering, operations, and commercial teams to deliver a foundational analytical framework, while providing near term analysis to continuously improve business impact and experience for our customers and suppliers.
- Perform deep-dive analysis on business impact, supplier/customer experience KPIs by leveraging analytics (SQL) to identify root causes behind performance issues and drive decision-making process at all levels (strategic, operational, tactical) through impact sizing, cost-benefit analysis, risk assessment, and other informed decision making methodologies
- Communicate findings with a succinct point of view and utilize compelling visualization tools (e.g. Looker, Data Studio, Tableau, etc.) to both the executive level and cross-functional teams; ensuring that these insights drive our strategies to deliver business impact.
- Work closely with Data Engineering and Analytics teams to build data warehouses / data layers and visualizations for both process health monitoring and executive level KPI reporting
- Analyze large and complex datasets, answer ambiguous questions, and develop recommendations to guide business decisions with senior leadership
- Partner with business and engineering stakeholders at various levels to identify key factors and requirements for each initiative, secure the necessary buy-in from leadership for project methodology, and build a 6-12 month roadmap with clear goals and milestones
Preferred Qualifications
- Familiarity with Python or R is preferred but not required