Data Scientist, North America Sort Centers, Amazon Transportation Services

Amazon Science; Bellevue (WA); On-site; USD 136,000 - 184,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Science is seeking a Data Scientist II to own the end-to-end ML/optimization cycle for NASC & TOM planning. You will design, build, and ship models that inform middle miles decisions, partnering with engineering and product teams to translate operational needs into measurable outcomes.

The role involves forecasting, network optimization, and GenAI initiatives, with strong emphasis on deployment, monitoring, and stakeholder communication to executive leadership.

Qualifications

• 2+ years of data scientist experience.
• 3+ years experience with SQL/Python or equivalent.
• 3+ years ML/statistical modeling experience.
• Experience applying theoretical models in production environments.
• Experience communicating technical concepts to non-technical audiences.

Responsibilities

• Design and implement ML and optimization solutions for forecasting and network problems.
• Drive end-to-end delivery from data exploration through training, evaluation, deployment and monitoring.
• Develop modeling patterns for forecasting and optimization with advanced techniques.
• Build robust validation, backtesting and leakage/bias detection pipelines.
• Collaborate with Data Eng and Software teams to productionize models and define interfaces.

Skills

SQL

Python

Statistical modeling

Time-series forecasting

ML algorithms

Communication

Education

Master's degree in STEM

Tools

AWS Suite (S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, EC2)

Job description

Description

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.

As a Data Scientist II, you will own the end-to-end Machine learning Operation cycle: Design, build, and ship machine learning and/or optimization models that directly shape Amazon's middle miles planning decisions. You will own end-to-end delivery — from problem framing with business partners, through modeling and validation, to deployment in internal model hosting platform and integration with downstream planning tools.

You Will Work On Problems Such As

• Long- and short-horizon forecasting
• Network and capacity optimization
• GenAI / agentic systems
• Defect prevention and adaptive planning

You will partner closely with Engineering, Product, Engineering, and stakeholders to translate ambiguous operational pain points into measurable model outcomes.

Key job 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.

Basic Qualifications

• 2+ years of data scientist experience
• 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
• Experience applying theoretical models in an applied environment
• Experience communicating technical concepts to a non-technical audience
• Proficiency in statistical modeling and machine learning — time-series forecasting, regression, tree-based methods, and deep learning.

Preferred Qualifications

• Master's degree in Science, Technology, Engineering, or Mathematics (STEM)
• Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
• Experience in a ML or data scientist role with a large technology company

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually