Executive Director / Director, Head of Applied Data and Analytics Office
On-site · Tokyo, Tokyo, Japan
Job Summary
Executive leadership role directing the design, development, and delivery of advanced analytics products and AI/GenAI capabilities across the organization. Responsible for translating business requirements into scalable analytics solutions, establishing enterprise-grade ML/AI product engineering practices, governance and risk management alignment, and delivering insights and analytics capabilities (e.g., Power BI, Databricks SQL) to senior leadership. Oversees MLOps, model lifecycle management, guardrails, and end-to-end deployment from concept to production, with emphasis on responsible AI, explainability, and value realization. Leads cross-functional teams across data science, data engineering, analytics, platform engineering, and risk/compliance functions; fosters engineering excellence, talent development, and stakeholder collaboration; and ensures delivery KPIs, product adoption, and operational uptime in a large financial services context.
Required Qualifications
- Bachelor’s degree in a quantitative, technical, or analytical discipline (e.g., Computer Science, Data Science, Statistics, Mathematics, Engineering)
- 15+ years of experience in data analytics, data science, AI/ML engineering, or technology delivery within large, complex financial institutions or technology companies
- Proven track record of leading end-to-end analytics delivery — from ideation and development through to production deployment and operationalisation at scale
- Deep hands-on understanding of modern analytics and AI platforms, including Azure, Databricks, Power BI, Python, and cloud-native architectures
- Strong knowledge of MLOps, CI/CD, model lifecycle management, and production-grade analytics engineering practices
- Exceptional stakeholder engagement and communication skills at senior leadership level
- Experience managing multi-disciplinary teams spanning data science, engineering, analytics, and platform functions
Desired Qualifications
- Bachelor’s degree in a quantitative, technical, or analytical discipline
- 15+ years of experience in data analytics, data science, AI/ML engineering, or technology delivery
- Proven track record of leading end-to-end analytics delivery
- Deep hands-on understanding of modern analytics and AI platforms (Azure, Databricks, Power BI, Python)
- Strong knowledge of MLOps, CI/CD, model lifecycle management
- Exceptional stakeholder engagement and communication at senior leadership level
- Experience managing multi-disciplinary teams spanning data science, engineering, analytics, and platform functions
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