Join Amazon's Customer Delivery Experience (CDE) Science Team as an Applied Scientist II to revolutionize global logistics through revolutionary research and innovation. Our team combines advanced machine learning and transportation logistics to improve delivery experiences for millions of customers worldwide. Working collaboratively with Amazon's core logistics teams, you will translate scientific innovations into practical solutions that drive meaningful improvements across our global fulfillment and delivery network.
Key job responsibilities
- Develop and implement predictive algorithms to identify and prevent delivery disruptions
- Design real-time machine learning systems for network-wide decision-making
- Create mathematical models optimizing speed, cost, and reliability
- Drive innovation in customer experience using generative AI
- Produce research reports and contribute to peer-reviewed publications
- Collaborate with cross-functional teams to implement scalable solutions
- Balance theoretical research with practical business applications
- Design and deploy production-quality components meeting engineering standards
- Work backwards from customer needs to determine scientific approaches
A day in the life
Your day combines intellectual discovery with real-world impact. You might start with a research initiative meeting, followed by analyzing complex datasets to identify delivery optimization opportunities. You'll collaborate with logistics teams to translate your findings into practical solutions, work on implementing machine learning models, and participate in cross-functional discussions to align scientific innovations with operational needs. The role offers a unique blend of academic-style research and immediate practical application, seeing your solutions directly impact millions of customer experiences.
About the team
The CDE Science team is a multidisciplinary group operating at the intersection of advanced analytics, applied research, and operational excellence within Amazon's global supply chain. We collaborate closely with Global Transportation Science, Supply Chain Optimization Technologies, and Amazon Fulfillment Technologies teams. Our culture emphasizes both scientific rigor and practical results, offering opportunities to publish in top-tier academic venues while driving meaningful improvements in service performance. We value diverse perspectives and innovative thinking in solving complex logistics challenges that directly impact customer experiences.- 5+ years of building machine learning models or developing algorithms for business application experience
- PhD, or Master's degree and 5+ 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 professional software development- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF
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 hiring process, including support for the interview or onboarding process, please visit
https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/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.
