SCOT's Automated Inventory Management (AIM) Planning team is seeking a Business Intelligence Engineer who enjoys the challenge of diving into complex problems and solving the unsolvable to help our executives make impactful decisions.

In this role, you will support inventory management innovation, AIM Inventory Planning roadmap and system improvements to automate worldwide inventory management, and identify and drive long term free cash flow opportunities.

You will work closely with Scientists, Engineers and Product Managers to build scalable, high insight- high impact products and lead retail inventory planning cycles, to enable top-notch Amazon global retail inventory efficiency strategy within our rapidly growing, dynamic business and influence Amazon's inventory management decisions on a day-to-day basis.

Key job responsibilities
In this role you will…

• Collaborate with and influence a wide set of stakeholders, providing thought leadership, product expertise, and business insight.
• Own and execute retail inventory guidance planning cycles, as inputs into global Amazon financial plans and network plans
• Work across AIM Planning, PMs, Engineers, Scientists, Finance, and SCOT teams to deliver the Inventory Planning BIE Roadmap.
• Dive deep to create insights on how well Amazon is taking care of the customer as it relates to product availability and inventory levels
• Drive changes through insights to improve a wide range of internal products that impact planning, buying and sourcing.
• Develop improvements and invent new ways to look at / trends via an internal worldwide customer portal.
• Interface with cross-functional teams to build centralized tools that will allow for rapid defect detection and repair.
• Partner with Engineers and Software Engineers to design products and systems to transform and store billions of items using AWS redshift
• Explore/analyze and work with Product Managers to understand customer behaviors, spot system defects, and benchmark our ability to serve our customers
• Design and implement technical solutions with an appropriate analytics strategy and data set design; make technical trade-offs for long-term / short-term needs; and drive best practices in operational excellence, data modelling, and analysis.