Applied Scientist Ii, Amazon Stores Economics and Science (seas)

Amazon Amazon · Big Tech · Mountain View, CA · Applied Science

Applied Scientist role focused on building and delivering state-of-the-art science and engineering solutions for Amazon's Stores business, leveraging machine learning, optimization, and economics to improve business metrics. The role involves developing and maintaining scientific models, benchmarks, and services, and deploying solutions in partnership with product teams.

What you'd actually do

  1. build and deliver state-of-the-art science and engineering solutions to improve our Stores business
  2. identify bottlenecks in our business, conceive new ideas to overcome those challenges, and deploy scientific solutions in partnership with product teams
  3. developing and maintaining the scientific models, benchmarks, and services

Skills

Required

  • PhD, or Master's degree and 4+ 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 any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Nice to have

  • 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
  • Experience using Unix/Linux
  • Experience in professional software development

What the JD emphasized

  • building models for business application experience
  • publications at top-tier peer-reviewed conferences or journals

Other signals

  • applying expertise in science and engineering to move from local to global optima in methods, models, and software
  • applying frontier science
  • developing and maintaining the scientific models, benchmarks, and services
  • deploy scientific solutions in partnership with product teams