Data Scientist, Amazon Leo Global Planning, Amazon Leo

Amazon Amazon · Big Tech · Bellevue, WA · Data Science

This role focuses on building and deploying machine learning models for global demand forecasting in the context of Amazon Leo's satellite broadband initiative. The Data Scientist will integrate data from various sources, develop bandwidth usage models, and ensure seamless integration with capacity planning systems. They will also contribute to the technical roadmap and evaluate AI systems, with a focus on assessing GenAI model performance.

What you'd actually do

  1. Work cross-functionally with product, business development, and various technical teams (engineering, science, simulations, etc.) to execute on the long-term vision, strategy, and architecture for the science-based global demand forecast.
  2. Design and deliver modern, flexible, scalable solutions to integrate data from a variety of sources and systems (both internal and external) and develop Bandwidth Usage models at granular temporal and geographic grains, deployable to Leo traffic management systems.
  3. Work closely with the capacity planning science team to ensure that demand forecasts feed seamlessly into their systems to deliver continuous optimization of resources.
  4. Lead short and long terms technical roadmap definition efforts to deliver solutions that meet business needs in pre-launch, early-launch, and mature business phases.
  5. Synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to drive change across Amazon Leo.

Skills

Required

  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • 1+ years of guiding and coaching a group of researchers experience
  • 1+ years of working with or evaluating AI systems experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
  • Experience applying theoretical models in an applied environment

Nice to have

  • Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in Python, Perl, or another scripting language
  • Experience in a ML or data scientist role with a large technology company
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience working on multi-team, cross-disciplinary projects
  • 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

  • working with or evaluating AI systems
  • defining and creating benchmarks for assessing GenAI model performance

Other signals

  • Develop Bandwidth Usage models
  • demand forecasts feed seamlessly into their systems
  • technical roadmap definition efforts
  • working with or evaluating AI systems
  • defining and creating benchmarks for assessing GenAI model performance