Group Product Manager, Data, Analytics & AI
Listed on 2026-10-10
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IT/Tech
AI Business & Operations, Business Intelligence, Business Systems & Technology Analysis, Data Analyst -
Business
AI Business & Operations, Business Intelligence, Business Systems & Technology Analysis, Data Analyst
Group Product Manager, Data, Analytics & AI Primary Location Los Angeles Possible Hiring Locations Los Angeles Department 0940 - E&IT Admin & Strategy
The Group Product Manager, Data, Analytics & AI leads the effort of defining the vision, strategy, roadmap, and lifecycle management of ICANN's enterprise data, analytics, artificial intelligence, reporting, and integration capabilities. This role treats enterprise data and AI capabilities as strategic products, ensuring they are aligned with business priorities, deliver measurable organizational value, and enable informed decision-making across the organization.
The role partners closely with business stakeholders, Enterprise Architecture, Enterprise Applications, Software Engineering, Security, and Data & AI teams to deliver trusted, scalable, and business-focused data capabilities. The Group Product Manager is responsible for maximizing the value of ICANN's investments in enterprise data, analytics, AI, reporting, integrations, and data governance while ensuring solutions remain aligned with organizational priorities and enterprise standards.
Key Responsibilities and Duties Product Strategy and Roadmap- Define strategy, roadmap, and investment priorities for ICANN's enterprise data, analytics, AI, reporting, and integration products.
- Treat enterprise data capabilities as products with defined roadmaps, measurable outcomes, and continuous improvement objectives.
- Develop product strategies aligned with organizational priorities, business capabilities, and technology strategy.
- Identify opportunities to leverage data, analytics, automation, and AI to improve organizational effectiveness and decision-making.
- Own the portfolio of enterprise data products, reporting platforms, analytics capabilities, dashboards, and business intelligence services.
- Partner with business stakeholders to define reporting, analytics, and decision-support priorities.
- Drive adoption of self-service reporting and analytics capabilities.
- Ensure enterprise reporting and analytics products provide trusted, timely, and actionable information.
- Define and manage the roadmap for AI-enabled business capabilities and enterprise AI products.
- Identify, evaluate, and prioritize AI use cases that improve business processes, workforce productivity, operational efficiency, and organizational outcomes.
- Partner with Enterprise Architecture and Security teams to ensure AI capabilities align with enterprise standards, governance, and responsible AI practices.
- Monitor emerging AI technologies and identify opportunities to deliver business value through AI innovation.
- Partner with business stakeholders to establish data ownership, stewardship, and governance practices.
- Define product requirements that improve data quality, consistency, accessibility, and trustworthiness.
- Support development of enterprise data standards, metadata practices, and master data strategies.
- Ensure data products align with organizational governance, privacy, compliance, and security requirements.
- Define product roadmaps and business priorities for enterprise integrations and data exchange capabilities.
- Partner with Enterprise Architecture and Engineering teams to establish integration priorities, API capabilities, and enterprise interoperability strategies.
- Identify opportunities to simplify integrations, improve data availability, and reduce manual processes through automation.
- Partner with business leaders to understand reporting, analytics, AI, and data needs.
- Translate business requirements into prioritized product roadmaps and measurable outcomes.
- Serve as the primary business relationship manager for enterprise data and analytics capabilities.
- Facilitate prioritization of competing requests while balancing organizational value, technical feasibility, and strategic alignment.
- Define success measures and key performance indicators for data, analytics, AI, and reporting products.
- Monitor adoption, utilization, business value, and customer satisfaction.
- Develop executive dashboards and reporting that demonstrate value realization and product performance.
- Continuously evaluate opportunities to improve products based on user feedback, operational metrics, and evolving business needs.
- Collaborate with Product Management, Enterprise…
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