Data Scientist I, Pxt Central Science

Amazon Amazon · Big Tech · San Francisco, CA · Data Science

Data Scientist role focused on applying statistical, machine learning, or GenAI methodologies to enhance employee experience within Amazon's People Experience and Technology (PXT) organization. The role involves translating business challenges into quantitative frameworks, extracting insights from data, and architecting scalable solutions.

What you'd actually do

  1. Own the design, development, and maintenance of scalable models and prototypes leveraging statistical, machine learning, or GenAI methodologies to enhance employee experience.
  2. Partner with scientists, engineers, and product leaders to solve for employee experience defects using scientific approaches, building new services and tools that deliverable measurable impact.
  3. Author and maintain detailed technical documentation related to the projects you drive.
  4. Communicate results to diverse audiences of varying technical background with effective writing, visualizations, and presentations
  5. Stay current with emerging methods and technologies, and implement them strategically to amplify the team’s impact.

Skills

Required

  • 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
  • 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Nice to have

  • Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
  • Experience working with or evaluating AI systems
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication

What the JD emphasized

  • scalable models and prototypes
  • statistical, machine learning, or GenAI methodologies
  • employee experience defects
  • scientific approaches
  • new services and tools
  • measurable impact
  • emerging methods and technologies

Other signals

  • Leveraging statistical, machine learning, or GenAI methodologies
  • Enhance employee experience
  • Apply data science to mission