Stores Economics and Science (SEAS) is an interdisciplinary science and engineering team in Amazon's Stores organization with a peak-jumping mission: we leverage frontier science to collaborate with partner teams. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. In 2025, we are focused on developing emerging machine learning solutions (e.g., LLMs and causal ML) to understand substitutable products on Amazon.
We are looking for an Applied Scientist to build and deliver solutions to improve our Stores business. In this role, you will work in a team of scientists, economists, and engineers with backgrounds in machine learning, NLP, IR, statistics, and economics to identify bottlenecks in our business, conceive new ideas to overcome those challenges, and deploy scientific solutions in partnership with product teams. Your responsibilities include developing and maintaining the scientific models, benchmarks, and services. Graduate education or hands-on experience in machine learning, optimization, causal inference, Bayesian statistics, deep learning, or other quantitative scientific fields is a big plus. To be successful in this role, you should be a quick learner and comfortable with a high degree of ambiguity.
