Applied Scientist: Cloud Cost Insights & Optimization

Amazon Web Services (AWS)

Seattle (WA)

On-site

USD 142,800 - 193,200

Full time

14 days+

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Job summary

Amazon Web Services, Inc. in Seattle is seeking an Applied Scientist for AWS Insights & Optimization to develop sophisticated algorithms that analyze and learn from hundreds of billions of customer cost, usage, and utilization events daily.

You will power cost anomaly detection, cost forecasting, rightsizing across EC2, EBS, Lambda, ECS, RDS, and Aurora, and contribute to AI-powered agent experiences that help customers optimize spend.

Qualifications

  • 3+ years of building models for business applications.
  • PhD, or Master’s degree and 4+ years of CS, CE, ML or related field experience.
  • Experience publishing patents or papers at top-tier conferences or journals.
  • Experience programming in Java, C++, Python or related languages.
  • Experience in algorithms, data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or HPC

Responsibilities

  • Own models end-to-end—from problem formulation to production deployment.
  • Collaborate with scientists, engineers and product teams to improve and build models.
  • Define evaluation metrics and testing strategies for production readiness.
  • Influence stakeholders to solve real-world customer problems with algorithms.

Skills

Modeling
Programming: Java/C++/Python
Data mining
Numerical optimization
Parallel & distributed computing
Cost forecasting

Education

PhD
Master's +4 years CS/CE/ML

Tools

Unix/Linux

Job description

Amazon Web Services, Inc. in Seattle is seeking an Applied Scientist for AWS Insights & Optimization to develop sophisticated algorithms that analyze and learn from hundreds of billions of customer cost, usage, and utilization events daily.

You will power cost anomaly detection, cost forecasting, rightsizing across EC2, EBS, Lambda, ECS, RDS, and Aurora, and contribute to AI-powered agent experiences that help customers optimize spend.

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