Applied Scientist, AWS Insights & Optimization

AWS Insights & Optimization is looking for an Applied Scientist to help develop sophisticated algorithms and models that involve analyzing and learning from over 540 billion customer cost, usage, and utilization events daily. We use this data to power cost anomaly detection, cost forecasting, rightsizing recommendations across seven compute services, Savings Plans optimization, and AI-powered conversational experiences that help customers understand and optimize their AWS spend. Our team's vision is to be the world's provider of intelligent AWS cloud financial management, where customers can understand, control, and optimize usage of AWS products. We sit at the nexus of all AWS services and interact directly with end-customers, building relationships with teams across AWS to ensure we offer a secure and reliable experience that builds trust and provides intelligent insights.

Own models end-to-end — from problem formulation through experimentation to production deployment.

Work on cost anomaly detection (decomposition, detection, and root cause attribution), time-series forecasting, rightsizing engines for EC2, EBS, Lambda, ECS, RDS, and Aurora, LLM evaluation science for AI-powered agent experiences, or agent memory architectures.

Work closely with applied scientists, software engineers, and product teams to enhance existing models and build new ones that solve challenging customer problems.

Drive implementation of proposed models, establish testing strategies to validate them before and after production, and define evaluation metrics that determine whether capabilities meet the quality bar.