Have you ever ordered a product on Amazon and when that box-with-the-smile arrives, you wonder how it got to you so fast?
Ever wondered where it came from and how much it cost Amazon? Wondered how Amazon designs its transportation network to scale and reliably deliver hundreds of millions of packages to customer's doorsteps? If so, Amazon's Trans Systems Analytics & Customer Experience (TSA & CX) team is for you.
We use mathematical models, business analytics, algorithm design and statistics to improve decision-making capabilities across Operations and Amazon Logistics. Our objective is to create a reference for what the ideal transportation network looks like and build scalable audit mechanisms to assess and reduce the gap to the current network. We do so by treating system defects as gifts and solving anomalies in systems and their behavior to achieve business goals.
We are based out of the EU headquarters in Luxembourg and looking for a talented and motivated Senior Applied Scientist to innovate and enhance our outbound network optimization and management products. In this role, you will solve highly visible problems that are important for senior leaders across organizations.
We want you to solve capacity optimization problems and re-define the way we approach resource allocation. You are someone:
- PhD, or Master's degree
- Experience programming in Java, C++, Python or related language
- Experience in applied research
- Background in Operations Research highly desirable or experience in optimization of resource allocation
- Experience in building models for business applications
- Able to communicate highly complex concepts to a business audience.
- Hands-on experience leading large-scale big data and analytics projects.
- Experience applying theoretical models in an applied environment.
- Experience diving into data to discover hidden patterns and conducting error/deviation analysis.
- Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2.
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.
* Le salaire de référence se base sur les salaires cibles des leaders du marché dans leurs secteurs correspondants. Il vise à servir de guide pour aider les membres Premium à évaluer les postes vacants et contribuer aux négociations salariales. Le salaire de référence n’est pas fourni directement par l’entreprise et peut pourrait être beaucoup plus élevé ou plus bas.