Research Scientist, Operational Efficiency, AET Planning and Analytics Science
Core
Building simulation, optimization, and causal inference models to automate workforce scheduling, hiring, and task assignment for Amazon's 1.5M+ employees.
Role type
Research Scientist (Operations Research & Causal Inference)
Builds
Contact center simulators, scheduling optimizers, and experiment frameworks for HR services and back-office operations.
Domain
Human Resources Operations / Workforce Management / Operations Research
Deliverable
production ML models
Required skills
Operations research, causal inference, statistical modeling, machine learning, simulation modeling, optimization, experimental design
Preferred skills
Causal Bayesian networks, potential outcomes, A/B testing, quasi-experiments, consulting with senior leadership
Technologies
R, MATLAB, Python
Responsibilities
Design and build simulation and optimization models for workforce scheduling and task assignment; Develop causal inference frameworks to measure policy impact; Collaborate with senior leaders to translate analytical findings into staffing and resource allocation strategies; Push boundaries by combining operations research with machine learning and generative AI.
Seniority
Senior, hands-on IC
