Applied Scientist II: Network Demand Forecasting & Capacity

Amazon Web Services (AWS); Seattle (WA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Job summary

Amazon Data Services, Inc. in Seattle is seeking an Applied Scientist to build and validate ML models for network demand forecasting, topology planning, and capacity optimization.

You will collaborate with network engineers, software developers, and supply chain specialists to translate complex infrastructure problems into production-ready solutions. You will drive hypothesis-driven research to inform business roadmap decisions, deliver low-latency forecast predictions, and own projects

Qualifications

• PhD or Masters with 4+ years in CS/CE/ML or related field.
• Experience publishing in top-tier conferences or journals.
• Experience programming in Java, C++, Python or related language.
• Experience building models for business applications.

Responsibilities

• Build and validate ML models for network demand forecasting, topology planning, and capacity optimization.
• Collaborate with network engineers, software developers, and supply chain specialists to translate problems into production-ready scientific solutions.
• Drive hypothesis-driven research to inform business and product roadmap decisions for network traffic modeling.
• Build production systems to deliver low-latency network forecast predictions and scale throughput.
• Own problems end-to-end, translating needs into coherent projects with long-term impact.

Skills

Java/C++/Python

ML modeling

Distributed computing

Education

PhD or MS + 4+ years CS/CE/ML

Job description

Amazon Data Services, Inc. in Seattle is seeking an Applied Scientist to build and validate ML models for network demand forecasting, topology planning, and capacity optimization.

You will collaborate with network engineers, software developers, and supply chain specialists to translate complex infrastructure problems into production-ready solutions. You will drive hypothesis-driven research to inform business roadmap decisions, deliver low-latency forecast predictions, and own projects