Data Scientist: End-to-End Analytics for Transportation Networks

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

Job summary

Amazon Science seeks a Data Scientist to own the full analytical lifecycle from identifying business needs to productionizing models that inform transportation operations. You will build scalable data tools, develop simulations and optimization models, and narrate insights through compelling visualizations for leadership and cross-functional teams.

The role requires collaboration with Applied Scientists, Software Engineers, and Product Managers to deliver data-driven decisions at scale in the

Qualifications

• 2+ years of data scientist experience.
• 3+ years of SQL, Python or R/SAS/M$atlab experience.
• 3+ years of ML/statistical modeling experience.
• Experience applying theoretical models in an applied environment.
• Experience with big data processing and presenting large datasets.
• Bachelor's degree required.

Responsibilities

• Own end-to-end analytical lifecycle from problem framing to results narration.
• Design production-grade analytical tools and interactive data products.
• Develop and enhance simulation and optimization models for network planning.
• Architect efficient data pipelines and real-time visualization support.
• Build storytelling artifacts to communicate network dynamics to stakeholders.
• Collaborate with scientists, engineers, and product managers.

Skills

Data science experience

SQL

Python

Machine learning

Big data processing

Data storytelling

Education

Bachelor's degree

Master's degree

Tools

S3

Redshift

Sagemaker

EMR

Kinesis

Lambda

EC2

D3.js

Deck.gl

Job description

Amazon Science seeks a Data Scientist to own the full analytical lifecycle from identifying business needs to productionizing models that inform transportation operations. You will build scalable data tools, develop simulations and optimization models, and narrate insights through compelling visualizations for leadership and cross-functional teams.

The role requires collaboration with Applied Scientists, Software Engineers, and Product Managers to deliver data-driven decisions at scale in the