We are looking for a science leader who is able to provide structure around complex business problems, work with machine learning scientists to estimate and validate their models on large scale data, and who can help business and tech partners turn the results of their analysis into policies, programs, and actions that have a major impact on Amazon's business. We are looking for creative thinkers who can combine a strong economic toolbox with a desire to learn from others, and who know how to execute and deliver on big ideas.
At the senior level, we expect you be able to own the development of scientific models and to manage, in close collaboration with scientists and engineers, the data analysis, modeling, and experimentation that is necessary for estimating and validating your model. You will need to work with our business partners to communicate the properties of your analysis/modeling and be able to work to incorporate their feedback and requests into your project. Experience in applied economic analysis is essential, and you should be familiar with modern tools for data science and business analysis.
About the team
The Stores Economics and Science (SEAS) organization uses economics, statistics, and machine learning to understand and design the complex economy of Amazon's network of buyers and sellers. We are an interdisciplinary team, committed to use of cutting edge technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon. Our team is composed in equal parts of software engineers and scientists trained in diverse fields including ML, robotics, computer vision (CV), natural language processing (NLP), distributed systems and econometrics.
Our mission is to drive adoption of AI science and technology across Amazon by partnering with business teams on science-heavy problems, incubating products with high AI research risk, reducing friction and manual effort with AI tooling, and raising the scientific bar across all teams at Amazon.