Sr. Applied Science Manager, Stores Economics and Sciences

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

This role is for a Senior Applied Science Manager on the Stores Economics and Science team at Amazon. The team uses economics, statistics, and machine learning to understand and design Amazon's buyer and seller economy. The manager will provide structure for complex business problems, work with ML scientists to validate models, and help partners translate analysis into impactful actions. The role requires experience in building large-scale ML/AI solutions, leading scientists, and developing junior talent.

What you'd actually do

  1. provide structure around complex business problems
  2. work with machine learning scientists to estimate and validate their models on large scale data
  3. 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
  4. hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track

Skills

Required

  • 10+ years of building large-scale machine learning and AI solutions at Internet scale experience
  • Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
  • Experience building large-scale machine learning and AI solutions at Internet scale
  • Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
  • Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track

Nice to have

  • 10+ years of practical work applying ML to solve complex problems for large-scale applications experience
  • 5+ years of hands-on work in big data, machine learning and predictive modeling experience
  • 5+ years of people management experience
  • PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
  • Experience in practical work applying ML to solve complex problems for large scale applications
  • Experience working with big data, machine learning and predictive modeling

What the JD emphasized

  • 10+ years of building large-scale machine learning and AI solutions at Internet scale experience
  • Experience building large-scale machine learning and AI solutions at Internet scale
  • Experience in practical work applying ML to solve complex problems for large scale applications

Other signals

  • uses economics, statistics, and machine learning
  • build solutions for some of the toughest business problems
  • lead experienced scientists
  • develop junior members