Applied Science Manager, JCI Measurement and Optimization Science Team

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

Basic Qualifications

- 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

Preferred Qualifications

- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
- Experience communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs

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