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Data Scientist III, Supply Chain Optimization Technologies; SCOT), Inbound Planning Science

Job in Bellevue, King County, Washington, 98009, USA
Listing for: Amazon
Full Time position
Listed on 2026-07-13
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst, Data Science Manager, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 159200 - 215300 USD Yearly USD 159200.00 215300.00 YEAR
Job Description & How to Apply Below
Position: Data Scientist III, Supply Chain Optimization Technologies (SCOT), Inbound Planning Science

Data Scientist III, Supply Chain Optimization Technologies (SCOT), Inbound Planning Science

Job :  |  Services LLC - A57

Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? We are looking for a Data Scientist who will be responsible to develop scientific solutions to optimize our inbound fulfillment strategy across multiple networks and global regions, to maximize our Customer Experience and minimize our cost to serve and carbon footprint.

You will partner with the worldwide scientific community to help design the optimal fulfillment strategy for Amazon. You will also collaborate with technical teams to develop optimization tools for network flow planning and execution systems. Finally, you will also work with business and operational stakeholders to influence their strategy and gather inputs to solve problems.

You will work in a fast-paced environment that requires you to be detail-oriented and comfortable in working with science, business, and technical teams.

Key job responsibilities
  • Design and develop mathematical models to optimize inventory placement and product flows.
  • Design and develop statistical and optimization models for planning Supply Chain under uncertainty.
  • Manage several, high impact projects simultaneously.
  • Consult and collaborate with business and technical stakeholders across multiple teams to define new opportunities to optimize our Supply Chain.
  • Communicate data-driven insights and recommendations to diverse senior stakeholders through technical and/or business papers.
  • Leverage LLMs to improve explainability of our optimization solutions and drive engagement from supply chain planners across the world.
Basic Qualifications
  • Bachelor's degree
  • Experience with statistical models e.g. multinomial logistic regression
  • Experience working as a Data Scientist
  • Experience with data scripting languages (e.g. SQL, Python, R, etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
Preferred Qualifications
  • Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
  • Experience with data visualization using Tableau, Quicksight, or similar tools
  • Experience managing data pipelines
  • Experience as a leader and mentor on a data science team

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit (Use the "Apply for this Job" box below). for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Salary:  -  USD annually (USA, WA, Bellevue)

Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at .

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