Applied Science Manager, JCI Measurement and Optimization Science Team
Amazon (AI roles) · Tokyo, JPN
No salary listed. Estimated from 353 salary-disclosed Operations roles on this board: $150K–$225K (interquartile range; estimate, not the employer's figure).
Apply at Amazon (AI roles)Find your warm intro on LinkedInAbout the role
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, financial simulation, forecasting, and GenAI agent development
-Partner with product, engineering, operations, and finance to translate science into operational impact
-Drive the integration of science models into AI tools — making causal reasoning accessible to non-technical stakeholders at scale
-Represent CtS science to VP-level leadership through MBR/QBR mechanisms and OP planning
At Amazon, you'll work alongside the latest AI and GenAI tools that are increasingly woven into how teams operate: from AI-powered capabilities that accelerate decision-making, to Generative AI that helps you focus on work that truly matters. You'll have opportunities and resources to develop AI fluency at your own pace, with continuous learning built into the culture. - Knowledge of ML, NLP, Information Retrieval and Analytics
- Master's degree in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field
- 3+ years of building machine learning models or developing algorithms for business application experience
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, financial simulation, forecasting, and GenAI agent development
-Partner with product, engineering, operations, and finance to translate science into operational impact
-Drive the integration of science models into AI tools — making causal reasoning accessible to non-technical stakeholders at scale
-Represent CtS science to VP-level leadership through MBR/QBR mechanisms and OP planning
At Amazon, you'll work alongside the latest AI and GenAI tools that are increasingly woven into how teams operate: from AI-powered capabilities that accelerate decision-making, to Generative AI that helps you focus on work that truly matters. You'll have opportunities and resources to develop AI fluency at your own pace, with continuous learning built into the culture. - Knowledge of ML, NLP, Information Retrieval and Analytics
- Master's degree in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field
- 3+ years of building machine learning models or developing algorithms for business application experience
More like this