Data Scientist I, Customer Delivery Excellence Science

Amazon • Bellevue, WA

7d

About The Position

Join Amazon's Customer Delivery Experience (CDE) Science Team as a Data
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.

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.

Requirements

• Bachelor's degree or above in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
• Experience communicating technical concepts to a non-technical audience
• 1+ years of experience building supervised learning models (regression, classification) from problem definition through deployment
• Proficiency in Python or R for data manipulation and statistical analysis, including libraries such as pandas, scikit-learn, or equivalent
• Strong SQL skills for data extraction and transformation from relational databases
• Experience with model evaluation techniques including cross-validation, performance metrics (RMSE, AUC, precision/recall), and statistical testing

Nice To Haves

• Experience working with or evaluating AI systems
• 2+ years of experience in data science or machine learning roles
• Experience with transportation, logistics, or supply chain optimization problems
• Familiarity with Amazon SageMaker, AWS services, or similar cloud ML platforms
• Experience with gradient boosting frameworks
• Knowledge of time-series forecasting or geospatial analysis techniques

Responsibilities

• Build and validate predictive models for delivery time estimation using historical delivery data, weather patterns, and traffic information
• Implement classification models to identify delivery exceptions and risk factors using established ML frameworks
• Apply feature engineering techniques to extract meaningful signals from transportation and logistics data
• Conduct exploratory data analysis on delivery performance metrics to identify improvement opportunities
• Create data visualizations and reports to communicate findings to operations partners
• 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

Benefits

• 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
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level