Sr. Manager, Applied Science, Marketing Measurement and Performance Science (maps)

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

Senior Manager, Applied Science for Marketing Measurement and Performance Science (MAPS) at Amazon. This role focuses on building scalable ML and causal inference solutions to estimate marketing effectiveness and provide insights for marketing teams. It involves leading a team of scientists, developing end-to-end causal inference models, and influencing multi-billion dollar investment decisions. The role requires expertise in ML/DL, statistics, economics, and handling large datasets at scale, with a focus on delivering data-driven solutions that impact business strategy and customer behavior.

What you'd actually do

  1. Apply your expertise in ML/DL and statistical modeling to develop solutions and systems that describe how Amazon’s marketing campaigns impact customers’ actions
  2. Own the end-to-end development of novel causal inference models that address the most pressing needs of our business stakeholders and help guide their future actions
  3. Recruit high performing Economist, Applied Scientists and BIEs to the team and provide mentorship.
  4. Establish team mechanisms, including team building, planning, and document reviews.
  5. Review and audit modeling processes and results from scientists within and outside your team

Skills

Required

  • ML/DL
  • statistical modeling
  • causal inference
  • large-scale data handling
  • Economics
  • data-wrangling
  • team leadership
  • mentorship
  • hiring
  • stakeholder management
  • problem definition
  • ambiguity tolerance

Nice to have

  • AWS
  • Hadoop
  • Spark
  • Pig
  • Hive
  • Java
  • C++
  • R
  • MATLAB
  • Python

What the JD emphasized

  • building large-scale machine learning and AI solutions at Internet scale
  • develop scalable ML and causal inference solutions
  • estimate the effectiveness of Amazon marketing efforts
  • provide actionable insights
  • affect investments to the size of billions of dollars
  • translate complex business problems into scientific challenge
  • deliver data driven solutions
  • experience using machine/deep learning at scale
  • strong analytical and communication skills
  • work with stakeholders and partners
  • apply your expertise in Economics, ML/DL, statistics, and data-wrangling
  • identify opportunities for further research
  • provide insights that drive larger initiatives
  • develop solutions and systems that describe how Amazon’s marketing campaigns impact customers’ actions
  • Own the end-to-end development of novel causal inference models
  • Review and audit modeling processes and results
  • Formalize assumptions about how our models are expected to behave
  • Identify new opportunities that are suggested by the data insights
  • 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 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
  • 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
  • Experience in practical work applying ML to solve complex problems for large scale applications
  • Experience working with big data, machine learning and predictive modeling
  • Experience in people management

Other signals

  • develop scalable ML and causal inference solutions
  • estimate the effectiveness of Amazon marketing efforts
  • provide actionable insights to the various marketing teams
  • develop systems that affect investments to the size of billions of dollars
  • translate complex business problems into scientific challenge
  • deliver data driven solutions
  • experience using machine/deep learning at scale
  • apply your expertise in Economics, ML/DL, statistics, and data-wrangling
  • identify opportunities for further research
  • provide insights that drive larger initiatives
  • develop solutions and systems that describe how Amazon’s marketing campaigns impact customers’ actions
  • Own the end-to-end development of novel causal inference models
  • Review and audit modeling processes and results
  • Formalize assumptions about how our models are expected to behave
  • Identify new opportunities that are suggested by the data insights
  • building large-scale machine learning and AI solutions at Internet scale
  • applying ML to solve complex problems for large-scale applications
  • working with big data, machine learning and predictive modeling