- Lead the integration of the Inventory Operations Data Analytics teams into one organization with a shared roadmap, shared prioritization process, and clear ownership and expectations.
- Build and defend a unified data strategy for Inventory Operations: the pipelines and architecture that make data trustworthy, and the reporting and visualization layer that makes it usable by decision-makers who are not analysts.
- Lead a combined organization of 10-15 team members, including a Manager of Data Analytics and individual contributors.
- Balance team leadership with execution to deliver high-quality results while hiring, developing, and retaining a high-performing team.
- Manage the weekly and monthly business review process for inventory data, including the metrics, the follow-up mechanism, and the discipline to keep it decision-focused rather than a status readout.
- Identify root causes through analytics and either drive the fix directly or work through the accountable partner to make the improvement repeatable and scalable, rather than a one-time solve.
- Reduce manual reporting load across the combined team by pushing toward automated, self-serve data products, and be explicit with your team and stakeholders about where AI and automation change how work gets done.
- Represent Inventory Operations data capability in cross-functional forums with Merchandising and Technology partners and escalate risks and tradeoffs to leadership before they become surprises.
- Establish a positive work environment conducive to collaboration and teamwork.
- Ensure team has the tools, resources, and information they need to be successful.
- Strategize with leadership to overcome potential stumbling blocks and resistance.
Requirements
- 8+ years of relevant experience with 3+ years leading teams, including direct leadership of both analytics/BI and data engineering functions, or demonstrated fluency in managing both.
- A track record of building highly functioning teams and leading through change
- Working fluency in both technical languages: BI and visualization tools (Tableau, Looker, or similar) and data engineering fundamentals (SQL, Python, ETL/ELT, cloud data warehousing, pipeline architecture).
- Outstanding executive communication and storytelling skills, with the judgment to know when a data engineering constraint needs to be translated into business terms for a non-technical audience.
- Strong analytic and root-cause skills paired with the ability to demonstrate the value of a solution, not just diagnose the problem.
- A history of building trust across functions and strong collaboration and influence skills.
- Comfort holding teams accountable to a shared standard and setting clear expectations across the team.
- Experience leading a mixed structure, some direct reports who are individual contributors and at least one who is a people manager, and a clear point of view on when a discipline needs its own management layer versus when it doesn't.
- Bachelor's degree or higher in Computer Science, Analytics, Supply Chain/Logistics, Business Administration, Economics, or a related field, or equivalent experience.
- Retail or supply chain experience strongly preferred, given the operational stakes of inventory decisions on customer experience.
Core Competencies
Demonstrates expertise in leading data analytics and engineering teams, with a focus on building trust, collaboration, and high-performance standards. Proficient in developing data strategies that enhance decision-making through effective reporting and visualization.
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