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Amazon

Applied Science Manager, JCI Measurement and Optimization Science Team

Tokyo, JPN

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hirly's read of this role

Role family
Supply chain
Seniority
Lead / management
Country
JP
Work mode
On-site / unstated
First seen by hirly
27 Sept 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

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.

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

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Original posting on Amazon's site ↗

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