Applied Scientist II, Global Mile
Listed on 2026-07-16
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IT/Tech
Data Scientist, Data Analyst
Come and be a part of Amazon’s amazing growth story and innovation!
Amazon Global Mile Tech is chartered to build a comprehensive portfolio of products that provides Shippers end-to-end transportation, node processing and foundational capabilities to ship packages internationally across a global network of connected arcs and nodes in a variety of scenarios (imports, exports and trans shipments). There are millions of such packages, each with different attributes, delivery requirements and international commerce and customs constraints.
What results is a complex graph of source, intermediate and destination nodes with their arcs crossing international borders and associated with different costs and transit times. Accounting for all these constraints and maximizing the number of shipments shipped, while minimizing cost, providing a variety of customer delivery options and maximizing delivery performance is our primary focus.
We are building world class technology cutting across deep algorithmic problems, brand new tools that cater to multi-party business scenarios and challenging data models that are evolving very quickly. Our systems touch every single package that travels internationally which mandates building of highly available and scalable distributed systems. Besides technology, there are ample opportunities in the team to build domain expertise of international transportation and supply chain realms and get first-hand experience of the Amazon operations by interacting directly with our global internal and external partners, and of course the esteemed senior engineering talent pool.
We are looking for a highly talented applied scientist to be part of our science team in Bellevue, WA. In this role, you will partner with business and technical teams to design and document requirements, and develop technical strategies and software roadmaps for delivery of features. You will be part of a passionate group of scientists in optimizing large‑scale distributed technology solutions and also innovating new ideas and providing technology directions to our business in the domain of imports and exports logistics.
We have many key initiatives lined‑up to support our rapid evolution and growth of the international transportation network by solving some of the most challenging problems in this domain.
- Develop accurate and scalable optimization, mathematical programming, and heuristic methods to solve the most challenging transportation problems.
- Lead and partner with engineering and operations teams to drive modeling and technical design for complex business problems in transportation.
- Lead complex modeling analyses to aid management in making key business decisions and setting new policies.
- Lead exploration of reinforcement learning techniques to augment optimization algorithms.
We value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
BenefitsLearn more about our benefits here: (Use the "Apply for this Job" box below).-stock
Basic Qualifications- 3+ years of building models for business application experience
- PhD, or Master’s degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top‑tier peer‑reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‑performance computing
- Experience using Unix/Linux
- Experience in professional software development
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and…
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