Data Scientist, Supply Chain Placement Analytics
il y a 2 semaines
Master's degree in Operations Research, Statistics, Applied Mathematics, Engineering, Computer Science or related field
- Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)
- Experience with big data technologies and familiar with the techniques and limitations of observational studies
Have you ever ordered a product on Amazon and wondered how it got delivered to you so fast? In the Amazon EU Supply Chain team, we are passionate to drive innovation on behalf of our customers to improve product availability and speed while reducing costs and carbon emissions. This role will give you a unique view into Amazon systems, processes and operations, allowing you to collaborate with planning, operations and 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
- 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
- Build scientific artifacts that support decision making of strategic and tactical Supply Chain planning teams, using appropriately complex Data Science techniques
- 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
- Develop the analytics required to visualize opportunities and measure success
- Research, develop, document and present new opportunities to all levels of Supply Chain, Finance, FBA and Retail leadership
Luxembourg, LUX
- PhD in Operations Research, Statistics, Applied Mathematics, Engineering, Computer Science or related field
- Experience as a data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources
- Experience with AWS Solutions, including EC2, S3, Redshift, EMR (or Hadoop)
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