Applied Scientist I, Customer Delivery Excellence Science
Location
Bellevue, WA
Job Type
Full-time
Category
other-general
Posted
June 09, 2026
Description
Join Amazon's Customer Delivery Experience (CDE) Science Team as a Applied Scientist I to improve global logistics through data-driven modeling and analysis. Our team applies advanced machine learning and statistical techniques to enhance delivery experiences for millions of customers worldwide. Working collaboratively with Amazon's logistics operations teams, you will implement proven ML solutions and contribute to continuous improvements across our global fulfillment and delivery network.
Key job responsibilities
- Build and validate predictive models for delivery time estimation using historical delivery data, weather patterns, and traffic information
- Implement models to identify delivery exceptions and risk factors using established ML frameworks
- Partner with logistics operations teams to understand business requirements and translate them into modeling approaches
- Document model methodologies, assumptions, and limitations for team knowledge...
Join Amazon's Customer Delivery Experience (CDE) Science Team as a Applied Scientist I to improve global logistics through data-driven modeling and analysis. Our team applies advanced machine learning and statistical techniques to enhance delivery experiences for millions of customers worldwide. Working collaboratively with Amazon's logistics operations teams, you will implement proven ML solutions and contribute to continuous improvements across our global fulfillment and delivery network.
Key job responsibilities
- Build and validate predictive models for delivery time estimation using historical delivery data, weather patterns, and traffic information
- Implement models to identify delivery exceptions and risk factors using established ML frameworks
- Partner with logistics operations teams to understand business requirements and translate them into modeling approaches
- Document model methodologies, assumptions, and limitations for team knowledge...