Data Scientist II: Forecasting & Network Optimization

Amazon Inc.; Factoria (WA); On-site; USD 136,000 - 184,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon.com Services LLC is seeking a Data Scientist II to own the end-to-end machine learning operation cycle, from problem framing with business partners through modeling, deployment, and monitoring in internal hosting platforms.

You will work on forecasting, network optimization, GenAI, and adaptive planning, partnering with Engineering teams to translate operational pain points into measurable model outcomes.

Qualifications

• 2+ years of data scientist experience
• 3+ years of data querying languages (SQL) or scripting languages (Python) or statistical software
• 3+ years of ML/statistical modeling experience
• Experience applying theoretical models in an applied environment
• Experience communicating technical concepts to non-technical audiences
• Proficiency in statistical modeling and ML—time-series forecasting, regression, tree-based methods, and deep learning

Responsibilities

• Design and implement complex ML and optimization solutions (forecasting, MIP/LP, simulation, Deep learning)
• Drive end-to-end delivery of scalable models from data exploration to deployment and monitoring
• Develop modeling patterns for forecasting and optimization (multivariate, hierarchical, causal-DAG)
• Build validation, backtesting, and monitoring pipelines; reduce leakage and bias
• Define model performance metrics tied to business outcomes
• Collaborate with Data Engineering to productionize models and define I/O contracts
• Present findings and tradeoffs clearly to stakeholders and leadership

Skills

SQL

Python

R/SAS/Matlab

Machine learning

Time-series forecasting

Education

Master's degree in STEM

Tools

AWS S3

Redshift

SageMaker

EMR

Kinesis

Lambda

EC2

Job description

Amazon.com Services LLC is seeking a Data Scientist II to own the end-to-end machine learning operation cycle, from problem framing with business partners through modeling, deployment, and monitoring in internal hosting platforms.

You will work on forecasting, network optimization, GenAI, and adaptive planning, partnering with Engineering teams to translate operational pain points into measurable model outcomes.