Senior Data Scientist, Pricing, Amazon Shipping, Amazon Shipping

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

Senior Data Scientist role focused on developing demand prediction and pricing models for Amazon Shipping's spot pricing system, utilizing ML and economic principles. The role involves automating price exploration, predicting prices to maximize capacity utilization, and incorporating models into production. Collaboration with business and software teams is key, as is educating non-technical leaders on complex modeling concepts.

What you'd actually do

  1. Combine ML methodologies with fundamental economics principles to create new pricing algorithms.
  2. Automate price exploration through automated experimentation methodologies, for example using multi-armed bandit strategies.
  3. Partner with other scientists to dynamically predict prices to maximize capacity utilization.
  4. Collaborate with product managers, data scientists, and software developers to incorporate models into production processes and influence senior leaders.
  5. Educate non-technical business leaders on complex modeling concepts, and explain modeling results, implications, and performance in an accessible manner.

Skills

Required

  • 5+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
  • 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor's degree and 8+ years of professional or military experience
  • Experience with statistical models e.g. multinomial logistic regression

Nice to have

  • 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
  • Experience managing data pipelines
  • Experience as a leader and mentor on a data science team

What the JD emphasized

  • end-to-end ownership
  • successfully delivering complex projects
  • communicating at that level

Other signals

  • pricing models
  • demand prediction
  • spot pricing
  • automated experimentation
  • multi-armed bandit