Data Scientist II, Middle Mile Transportation Science team

About the role

The NASC & TOM Science team owns Operations Research, Machine Learning, and AI projects across the North America Sort Center (NASC) and Transportation Operations Management (TOM) planning and operations organizations. We turn complex network, labor, and capacity problems into deployed models that drive multi-million-dollar planning decisions every day.

Responsibilities

• Design and implement complex ML and optimization solutions (forecasting, MIP/LP, simulation, Deep learning / foundation model)
• Drive end-to-end delivery of scalable models — from data exploration and feature engineering through training, evaluation, deployment, and post-launch monitoring
• Develop new modeling patterns and analytical frameworks for forecasting (multivariate, hierarchical, causal-DAG, model-chaining) and optimization
• Build robust model validation, backtesting, and monitoring pipelines; identify and eliminate sources of leakage, bias, and silent failure
• Define and own model performance metrics (e.g., WAPE) tied to business outcomes
• Partner with Data Engineering and Software Development to productionize models and define I/O contracts, packaging, and model CI/CD
• Excellent communication to present findings, tradeoffs, and recommendations clearly to stakeholders and senior leadership

Requirements

• Master's degree in Science, Technology, Engineering, or Mathematics (STEM)
• 2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 2+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
• Proficiency in statistical modeling and machine learning — time-series forecasting, regression, tree-based methods, and deep learning
• Demonstrated ability to communicate technical results to non-technical business audiences

Qualifications

• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience

Skills

• Strong programming skills in Python/R
• Experience with AWS services
• Statistical modeling and machine learning expertise
• Ability to communicate technical results to non-technical audiences

Benefits

Amazon offers comprehensive benefits including health insurance, retirement plans, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

Pay

The base salary range for this position is $136,000.00 - $184,000.00 USD annually.

Schedule

Full-time