Manager III, Applied Science, PXT Central Science
Core
Leading a multidisciplinary team of scientists to build causal predictive models for Amazon's workforce decisions, specifically for Tier 1 hourly populations.
Role type
Senior IC manager of applied science (causal inference & ML)
Builds
Causal predictive models and production systems for workforce strategy
Domain
Workforce analytics, causal inference, machine learning
Deliverable
production ML models
Required skills
Management of scientists/ML engineers, causal inference, machine learning, NLP, analytics, deep learning, computer vision, code quality standards, team building, stakeholder partnership
Preferred skills
Building ML models for business applications, developing complex software systems, delivering deep learning/ML/CV solutions to customers
Technologies
Deep learning, machine learning, computer vision, large language models, novel architectures
Responsibilities
Manage and develop a high-performing team of scientists, establish operating mechanisms and performance expectations, own hiring and talent strategy, set and execute the scientific vision for causal predictive modeling, establish standards for code quality and scalability, bridge economists, data scientists, and engineers, partner with stakeholders to drive adoption of science-informed strategy, distill complex findings into recommendations for senior leadership, define team structure and strategic direction
Seniority
Senior, hands-on IC with people leadership
