Sr. Applied Science, Agentic WorkSpaces (AAWS)
Core
Design, build, and optimize forecasting and optimization models for Amazon WorkSpaces to ensure efficient compute, storage, and networking resource allocation globally.
Role type
Senior Applied Scientist (Capacity Modelling & Optimization)
Builds
Amazon WorkSpaces cloud-based virtual desktop service
Domain
Cloud Infrastructure / Capacity Planning / Machine Learning
Deliverable
production ML models
Required skills
machine learning model development, neural deep learning methods, Java, C++, Python, causal modeling, probabilistic modeling, operations research, mathematical optimization, simulation systems, scenario planning, evaluation frameworks
Preferred skills
R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, large scale distributed systems (Hadoop, Spark)
Responsibilities
Define scientific strategy for capacity modelling, build demand forecasting models across multiple time horizons, design supply optimization frameworks, develop causal and probabilistic models, architect simulation and scenario planning systems, pioneer ML integration with operations research, establish evaluation and monitoring systems, influence organizational capacity strategy
Seniority
Senior, hands-on IC