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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 sharing
- Participate in code reviews and contribute to team best practices
- Seek feedback from senior team members on proposed solution approaches and methodologies

A day in the life
The CDE Science Team values diverse perspectives and believes the best models come from teams with varied backgrounds and experiences. You'll have an assigned mentor from day one, regular 1:1s with your manager, and access to Amazon's ML University for continued learning. We support a healthy work-life balance and encourage you to invest in your professional growth through conference attendance and internal science forums.

About the team
The Customer Delivery Experience (CDE) Science Team combines advanced machine learning with transportation logistics expertise to optimize delivery operations at scale. You'll work alongside data scientists, machine learning engineers, and operations partners to solve complex logistics challenges that directly impact customer satisfaction.