Data Scientist, Lm Simulations Engineering, Amzl Simulations & Analytics Engineering

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

Data Scientist role focused on designing and optimizing complex delivery networks using statistical and machine learning models, experiments, and simulations. The role involves owning the Data Science/ML roadmap, translating business challenges into mathematical models, and delivering scalable solutions.

What you'd actually do

  1. Design and execute large-scale experiments to uncover insights from complex datasets
  2. Build scalable, automated pipelines for data analysis, model development, validation, and deployment
  3. Develop advanced ML solutions including regression, clustering, simulation, neural networks, and optimization algorithms
  4. Partner with cross-functional teams to implement data-driven strategies and measure impact
  5. Validate findings against alternative approaches and key performance indicators

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
  • 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 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

  • advanced ML solutions
  • large-scale experiments
  • complex datasets
  • scalable, automated pipelines
  • model development, validation, and deployment

Other signals

  • develops statistical and machine learning models
  • designing global experiments
  • discover new ways to enhance the customer experience
  • translate ambiguous business challenges into mathematical models
  • contribute to discrete event simulations
  • deliver solutions that scale