This role, part of the Inbound & DC Flow team within our Supply Chain organization, is a pivotal leadership position responsible for driving service improvements, optimizing automation utilization, and accelerating the execution of our Staple Stock strategy and Network Optimization efforts. The leader in this role will partner cross‑functionally to elevate store service, improve productivity, and deliver meaningful long‑term financial impact. This position directly supports instock improvement, store inventory reduction, and long‑term labor savings. Additionally, it manages network optimization decisions for suppliers and items representing at least 50 million annual cases across the supply chain, enabling accelerated productivity savings in the years ahead. You’ll sweep us off our feet if: · You have prior experience in retail space with a preferred background in transformational roles from Replenishment, Supply Chain and Stores operations. · You have strong exploratory data analysis skills and ability to make analytical, data driven recommendations and solutions · You are experienced with languages used to manipulate data and draw insights from large data sets (SQL, Python etc.,) · You have strong story telling experience with data visualizations in Tableau, Looker, etc. · You have Compelling, persuasive oral and written communication skills and can build strong cross-functional rela tionships · You are comfortable with shifting priorities in fast moving environment You’ll make an impact by: · Partnering with business and product stakeholders to solve challenging business problems and identify trends and opportunities · Applying your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and provide actionable insights · Defining and evaluating key performance metrics for new product launches · Developing data visualizations to monitor and quantify the impact of the product initiatives and unique business challenges · Identifying new levers to help improve key financial data insights, understanding root causes for change in metrics · Collaborating with data stewards and data engineering team to gather and process right information from various sources · Working effectively cross-functionally and communicate data and insights to non-tech leadership team
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Job Type
Full-time
Career Level
Mid Level
Number of Employees
11-50 employees