Product Manager - AI
Summary
Senior Product Manager in Tokyo owning the end-to-end roadmap for hospitality revenue systems, evolving pricing engines toward autonomous AI-driven yield management. The role blends strategy, data analysis and financial modeling, hands-on delivery with ML engineers, and stakeholder management; bilingual Japanese/English fluency is required.
Responsibilities
Strategic Roadmap: Define the global vision for pricing and promotion suites, charting the path from manual tools to fully autonomous yield management agents.
Algorithmic Yield Optimization: Partner with Machine Learning Engineers to develop logic that optimizes key industry metrics like Average Daily Rate (ADR) and Revenue Per Available Room (RevPAR).
End-to-End Delivery: Oversee the full product lifecycle and lead agile execution for high-scale, high-transaction volume solutions.
Data-Driven Decision Making: Leverage extensive data analysis and financial modeling to prioritize features and diagnose issues related to conversion and revenue contribution.
Stakeholder Management: Act as a strategic bridge between Engineering, Business Development, Customer Success, and external partners.
Requirements
Qualifications:
Experience: 5+ years in B2B2C SaaS product management with a history of launching data-intensive products or algorithmic decision-making systems.
Outcome-Oriented Mindset: Ability to define success through commercial metrics such as ADR growth and conversion uplift.
Analytical Rigor: Expert-level comfort with data analysis and financial modeling.
Strategic & Tactical Balance: Proven ability to define high-level strategy while remaining willing to handle hands-on investigation and QA.
Language Skills: Professional fluency in both Japanese and English (Bilingual).
Operational Agility: Self-starter capable of thriving in fast-paced, globally distributed environments.
Preferred Qualifications:
Domain Expertise: 3+ years specializing in Revenue Management, Pricing Engines, or Travel Distribution.
AI & Yield Innovation: Experience utilizing Machine Learning or AI for automated yield management or demand forecasting.
Collaborative Engineering: Proven experience working alongside Data Science or Machine Learning engineers.
Benefits
Work Environment:
Hybrid Work: Offers a hybrid arrangement combining remote and in-office work.
Schedule: Standard working days are Monday through Friday.
Time Off: Saturdays, Sundays, and national holidays are observed.
Vacations: Year-end and New Year vacations (6 days from December 29 to January 3).
Financial & Social Benefits:
Commuting: Commuting allowance is paid in accordance with company regulations.
Insurance: Full social insurance provided (employment, health, and pension).