Sr. Business Intelligence Engineer, EU SC Placement Analytics
Amazon
DESCRIPTION
Have you ever ordered a product on Amazon and wondered how it got delivered to you so quickly? In the Amazon EU Supply Chain Placement Analytics and Engineering team, we are passionate to drive innovation on behalf of our customers to improve product availability and delivery speed while reducing costs and carbon emissions.
This role, part of the Crossdock (IXD) Placement Analytics team, will give you a unique view into Amazon processes and systems, allowing you to collaborate with operational, tactical and strategic planning as well as technical teams. If you are an advocate to understand complexity in detail to drive improvements at scale, with a proven track record of analyzing and diving deep in complex data to generate insights and business recommendations, we’d like to talk to you.
This position is ideally based out of our EU Headquarters in Luxembourg.
Key job responsibilities
- Design and own the right set of metrics to evaluate, audit and improve efficiency of (IXD) processes and placement systems
- Recommend improvements to the placement strategy using modelling and large datasets. You'll guide planning teams and other relevant stakeholders with regards to the mix of products to place in Amazon buildings, maximizing selection and reducing distance to customers
- Partner with technology teams to define key priorities to accommodate growing business needs and implement your recommendation in production through smart configurations in Amazon systems
- Research, develop, document and present new opportunities to all levels of Supply Chain, Finance, Fulfilled By Amazon (FBA) and Retail leadership
A day in the life
- Collaborate with a diverse team of Business Intelligence Engineers, Data Scientists, (technical) Program/Product Managers and Finance Analysts to generate insights that drive further innovation in our placement processes and systems
- Develop effective metrics that allow aggregate insights at scale across organizations
- Explore Amazon's advanced placement algorithms through anecdote deep dives to understand concrete root causes of suboptimal placement decisions
- Basis these deep dives, scale their findings to drive prioritization and alignment
- Conduct data driven experiments to accelerate innovation