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Jet // e-commerce destination
Hoboken, NJ, USA    Posted: Friday, February 14, 2020
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The ideal candidate has a demonstrated passion for working with data to creatively & tenaciously solve complex problems. Your ultimate goal is use data to drive the right business outcomes & build strong relationships with the Technology & Supply Chain Operations teams you partner

What youll be working on (Job Duties)

Modeling (35%):

  • Develop mathematical models to build data-driven decision-making systems for inventory
    optimization & allocation, improving the Supply Chain performance
  • Apply decision tree models, coupled with machine learning models & incorporating business owner insights, to improve accuracy of Forecasting Product demand in supply chain. Create supervised & unsupervised learning models to forecast demand for product that
    are completely new to Work with retail analytics teams to capture more data
    sources enabling better modeling


  • Solve & formulate multi-objective integer/linear programming optimization problems to
    improve key performance metrics & drive down cost across Walmarts supply chain.
  • Provide insightful analysis & make recommendations to management regarding cost savings and/or profitability improvement strategies; Work with operational management to identify areas of improvement & perform other special duties & projects
  • Improve & automate replenishment ordering model by analyzing several key inputs across the supply chain. Consolidate big data sets with millions of records, determine the optimal inventory order quantity to balance customer experience & companys operating costs

Data Collection & Reporting (25%):

  • Develop data visualization & reports for key metrics in Supply Chain inventory management: Item In-stock, Inventory Turns, Purchase Order Visibility, Forecasts, etc. These reports help executive leadership to track business performance & drives process improvement initiatives
  • Design & build scalable data pipelines across data warehouses (PostgreSQL, Teradata, Hive, etc.) using SQL to efficiently maintain years of historical data & allow analysts to easily access the data for analyses & modeling

Collaboration (5%):

  • Collaborates with cross functional teams to apply established & new analytical processes on
    diverse data sets to deduce insights & solve business/operational problems
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