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Sr Principal Applied Scientist, Last Mile Technology - Routing & Planning Science

Bellevue, WA, United States

Sr Principal Applied Scientist, Last Mile Technology - Routing & Planning Science The Last Mile (LM) Science organization serves two primary functions: (1) maintaining and enhancing the components which provide the essential intelligence in nearly every LM system, and (2) creating the science which will enable the continued growth of Amazon in the future. The systems used on a daily basis by the Last Mile to deliver packages from the station to the customer’s doorstep contains embedded models developed by the science team, or relies on inputs derived from these models. These models determine how efficiently Amazon can serve its customers and at what cost. The models developed by the Last Mile science team cover every aspect of the delivery process, including service area planning, network capacity management, resource scheduling, sortation and route planning, driver route assignment for optimal performance, and managing any on-road exceptions. These models are applied across multiple programs such as Amazon Logistics (AMZL), Fresh and Whole Foods, AMXL (Heavy & Bulky), Ship with Amazon (SWA), and more. Additionally, they support three delivery channels, namely Delivery Service Partner (DSP), Amazon Flex, and Hub Delivery Partner, and operate in 21 countries using different transportation modes, including driving, walking, and biking. While continually improving the existing operations, the science team must also be at the forefront of defining the future direction for Amazon. Amazon must constantly innovate new ways of servicing our customer better and faster, and improving the experience of delivery associates. Science has a key role in this respect and must be pushing the boundaries to develop more efficient ways of utilizing our existing capacity and resources as well as creating new means of delivery. This include alternative ways of planning routes which can be more efficiently executed by walkers for instance, defining delivery channel topology and partitioning the volume across those channels, or leveraging local knowledge through hyper local delivery channels or empowering route designers to define delivery sequences for complex addresses. This is the type of innovation and continual improvement required to grow the business from delivering 10B packages in 2023 to a projected 15B in 2028.

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The Senior Principal Applied Scientist drives the research strategy and deliverables which determines the long-term health and success of our business. This requires a full understanding of the business and the needs of our customers as well as a deep knowledge of the science and how it can be applied to balance the customer and driver experience against the long-term sustainability of the operations and the need for the organization to reduce costs through increased efficiency. In addition to the scientific aspects of the role, the Senior Principal Applied Scientist plays a crucial role in applying a scientific lens to the business decisions made within the last mile to ensures that the right tradeoffs are being made.

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We are open to hiring candidates to work out of one of the following locations:

Bellevue, WA, USA

Basic Qualifications

• Ph.D. in Artificial Intelligence, Computer Science, Machine Learning, Physics, Statistics, Applied Math or Operations Research

• 15 or more years applying deep learning, machine learning or statistical models to solving real-world problems in the industry

• Proficiency in C/C++, Java or Python

• Outstanding written and verbal communication skills

• Experience with guiding R&D strategy at an organization

• 10+ Publications in top peer-reviewed statistics, ML, OR, or applied math journals

• Proven record of innovation and strategic impact across teams

• Excellent interpersonal skills, and a can-do never give-up attitude

• Ability to work independently and as a part of a diverse team

• 15+ years of experience in transportation/Logistics decision support systems

• 5+ years in large language and foundational models

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $240,100/year in our lowest geographic market up to $350,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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