Applied Scientist, Stores Economics & Science (seas)

Amazon Amazon · Big Tech · Seattle, WA · Applied Science

Applied Scientist role focused on economics and science within Amazon's Stores organization, applying expertise in machine learning, NLP, IR, statistics, and economics to solve business problems related to cost-to-serve, selection optimization, and emerging machine learning. The role involves leading initiatives from research to production, developing and maintaining scientific models, and designing algorithms and mechanisms for supply chain and marketplace challenges.

What you'd actually do

  1. lead large-scale science initiatives from research to production
  2. translate complex business problems into mathematical frameworks
  3. design and implement large-scale algorithms for complex supply chain and marketplace problems
  4. design incentive-compatible mechanisms for marketplace challenges
  5. influencing technical strategy and roadmaps for complex initiatives

Skills

Required

  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • 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
  • 3+ years of building models for business application experience

Nice to have

  • Graduate education or hands-on experience in machine learning, optimization, causal inference, Bayesian statistics, deep learning, or other quantitative scientific fields
  • Experience using Unix/Linux
  • Experience in professional software development

What the JD emphasized

  • strong publication record in top-tier conferences/journals
  • experience coordinating cross-functional projects
  • Hands-on experience building science solutions to mechanism design problems

Other signals

  • develop and deploy scientific solutions
  • develop and maintain scientific models, benchmarks, and services
  • design and implement large-scale algorithms
  • design incentive-compatible mechanisms