Applied Scientist I, Customer Delivery Excellence Science

Amazon • Bellevue, WA

1d • Onsite

About The Position

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.

Requirements

• Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
• Experience with any programming language such as Python, Java, C++
• Knowledge of one or more ML Frameworks (e.g., PyTorch, TensorFlow) and ML methods including NLP models (BERT, GPT-2/3), computer vision-based models (object detection, image recognition), and text-based models (Seq2Seq, Topic modeling)
• Experience in SQL data manipulation
• Coursework or project experience in statistical modeling, machine learning, or deep learning

Nice To Haves

• Ph.D. in computer science, mathematics, statistics, machine learning or equivalent quantitative field
• Experience with AWS data services (e.g., SageMaker, S3, Redshift, EMR)
• Experience with distributed computing frameworks (e.g., Spark)
• Publications at peer-reviewed ML or AI conferences (e.g., NeurIPS, ICML, KDD)
• Experience with deep learning architecture design and model optimization techniques (e.g., pruning, quantization)
• Familiarity with A/B testing frameworks and experimentation design
• Experience in logistics, supply chain, or operations research domains

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

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
• sign-on payments
• restricted stock units (RSUs)

What This Job Offers

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