The North America Capacity Planning team in Amazon Stores' Supply Chain organization is charged with planning, managing, and optimizing the use of inbound, storage, and fulfillment capacity in North America. Optimal planning and usage of this capacity is critical in enabling us to deliver several billion items annually at continually lower costs and higher speeds. The decision space extends from tactical short-term actions (what capacity constraints do we face next week and how do we alleviate them?) to large-scale long-term strategy (what kind of fulfillment capacity should we invest in, where, over the next three years?). The team works in close partnership with several other business and tech teams to develop capacity plans, and ensure the delivery and optimal use of fulfillment capacity.

As a Principal Research Scientist in this team, you will interact with subject matter experts within and outside the team, as well as scientists in a range of partner organizations, to develop scientific models for capacity planning and optimization. You will leverage these models to influence senior leadership to make high-impact decisions that are critical to building Amazon's future supply chain. You will also be an active participant in the overall Amazon scientific community, generating intellectual capital, participating in reviews and conferences, publishing in internal and external venues, and incorporating scientific rigor in the team's practices.

Key job responsibilities
- Develop scientific models for large-scale fulfillment capacity planning under uncertainty
- Partner with stakeholder science teams for development and use of their scientific models for various aspects of capacity planning such as demand estimation, inventory flows, and multi-echelon supply chain management
- Develop strategic plans for long-term capacity investments, in close collaboration with subject matter experts within and outside the team
- Influence senior leadership on large-scale one-way capital and technological investments for designing our future fulfillment network
- Partner with scientists across Amazon in developing scientific models that jointly optimize the Amazon supply chain

BASIC QUALIFICATIONS

- 10+ years of tech industry or equivalent experience
- Experience with complex supply chains (>100 facilities, >1000 routes)
- PhD in a quantitative discipline such as operations research, industrial engineering, computer science, economics, or an equivalent quantitative field.

PREFERRED QUALIFICATIONS

- Experience working effectively with science, data processing, and software engineering teams
- Experience in working with and influencing business leaders in making high-impact one-way door decisions leveraging scientific and quantitative analysis

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 $170,500/year in our lowest geographic market up to $294,700/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.