Applied Science Manager, JCI Measurement and Optimization Science Team
Amazon
Full-time
other-general
Location
Tokyo, Japan, Japan
Posted
July 27, 2026
Job Description
Description
We are seeking an Applied Science Manager to lead the Cost-to-Serve science team within JCI MOST (Measurement and Optimization Science Team). This team builds the causal models, optimization systems, and AI-driven analytics that power Amazon Japan's CtS program — identifying where cost saving opportunities exist across the supply chain, explaining why they exist, and quantifying their dollar impact.
You will manage a team of applied scientists, economists, and data scientists working across causal inference, consolidation optimization, supply chain forecasting, and GenAI-powered analytics. Your team's work directly shapes how VP-level leadership makes investment decisions across CtS levers in Amazon Japan.
Key Responsibilities
-Lead and grow a team of scientists delivering causal models, optimization engines, and AI-driven insights for supply chain cost reduction
-Set the science roadmap and prioritize across workstreams: causal attribution,...
We are seeking an Applied Science Manager to lead the Cost-to-Serve science team within JCI MOST (Measurement and Optimization Science Team). This team builds the causal models, optimization systems, and AI-driven analytics that power Amazon Japan's CtS program — identifying where cost saving opportunities exist across the supply chain, explaining why they exist, and quantifying their dollar impact.
You will manage a team of applied scientists, economists, and data scientists working across causal inference, consolidation optimization, supply chain forecasting, and GenAI-powered analytics. Your team's work directly shapes how VP-level leadership makes investment decisions across CtS levers in Amazon Japan.
Key Responsibilities
-Lead and grow a team of scientists delivering causal models, optimization engines, and AI-driven insights for supply chain cost reduction
-Set the science roadmap and prioritize across workstreams: causal attribution,...