Data Scientist Ii, Amazon Stores Finance Science

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

Data Scientist II role focused on developing and building ML and statistical models for forecasting Amazon Stores' financials, aiming to improve financial decision-making and planning for senior leadership.

What you'd actually do

  1. Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models
  2. Working with technical and non-technical stakeholders across every step of science project life cycle
  3. Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models
  4. Innovating by adapting new modeling techniques and procedures
  5. Presenting research results to our internal research community

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
  • Experience applying theoretical models in an applied environment
  • Bachelor's degree

Nice to have

  • Experience in a ML or data scientist role with a large technology company
  • Experience working on multi-team, cross-disciplinary projects
  • Experience effectively communicating complex concepts through written and verbal communication
  • Master's degree
  • Experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems

What the JD emphasized

  • lead high visibility initiatives
  • develop new science-based forecasting methodologies
  • build scalable models
  • improve financial decision making and planning
  • build new ML and statistical models from the ground up
  • transform financial planning
  • creative problem solvers
  • draw on an expansive methodological toolkit
  • transform financial decision-making with science
  • versatile modeling skills
  • owning and extracting insights from data
  • learn from and alongside seasoned scientists, engineers, and business leaders
  • effectively translate technical findings into business action
  • industry standard ML models
  • production implementations for large-scale ML models
  • adapting new modeling techniques and procedures
  • Presenting research results to our internal research community
  • Experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems

Other signals

  • develop new science-based forecasting methodologies
  • build scalable models to improve financial decision making
  • build new ML and statistical models from the ground up