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Data Scientist, EU S/C, Supply Chain Science

Job ID: 2690936 | Amazon EU Sarl - A84


Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you?

We are looking for a Senior Data Scientist who will be responsible to develop cutting-edge scientific solutions to optimize our Pan-European fulfillment strategy, to maximize our Customer Experience and minimize our cost and carbon footprint.

You will partner with the worldwide scientific community to help design the optimal fulfillment strategy for Amazon. You will also collaborate with technical teams to develop optimization tools for network flow planning and execution systems. Finally, you will also work with business and operational stakeholders to influence their strategy and gather inputs to solve problems.

To be successful in the role, you will need deep analytical skills and a strong scientific background. The role also requires excellent communication skills, and an ability to influence across business functions at different levels.

You will work in a fast-paced environment that requires you to be detail-oriented and comfortable in working with technical, business and technical teams.

Key job responsibilities
- Design and develop mathematical models to optimize inventory placement and product flows.
- Design and develop statistical and optimization models for planning Supply Chain under uncertainty.
- Manage several, high impact projects simultaneously.
- Consult and collaborate with business and technical stakeholders across multiple teams to define new opportunities to optimize our Supply Chain.
- Communicate data-driven insights and recommendations to diverse senior stakeholders through technical and/or business papers.


- Experience working as a Data Scientist
- 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 machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance
- Experience applying theoretical models in an applied environment


- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company

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