Group Product Manager, Data, Analytics & AI

Icann; Los Angeles, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

ICANN seeks a Group Product Manager for Data, Analytics & AI to define the vision, strategy, and lifecycle of enterprise data capabilities, analytics, and AI solutions. You will lead cross-functional teams and align data products with governance, security, and organizational priorities.

You will partner with EA, Security, and business leaders to maximize value, drive adoption of self-service analytics, and deliver trusted, scalable data capabilities that support informed decision-making across

Qualifications

• Bachelor's degree and 10+ years in product management, data, analytics or BI.
• Strong knowledge of data governance, data quality, metadata, and master data concepts.
• Experience delivering enterprise-scale data/analytics/AI products.
• Ability to translate business needs into product roadmaps and measurable outcomes.

Responsibilities

• Define strategy, roadmap, and investment priorities for data, analytics, AI, reporting, and integration products.
• Own portfolio of enterprise data products, dashboards, and BI services; drive adoption of self-service analytics.
• Define AI roadmap and prioritize AI use cases to improve processes and productivity.
• Ensure governance, privacy, compliance, and security across data products.
• Lead cross-functional planning with IT, security, EA, and business stakeholders.

Skills

Enterprise data

Analytics products

AI product management

Stakeholder management

Product operating models

APIs and data exchange

Data governance

Leadership

Education

Bachelor's degree in CS/IT/Data Science/Engineering/Business

Tools

BI tools

Enterprise data platforms

Job description

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.

Data Products and Analytics

• 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.

Artificial Intelligence Product Management

• 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.

Data Governance and Information Management

• 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.

Business Partnership and Stakeholder Engagement

• 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.

Product Governance and Value Realization

• 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.

Leadership and Cross-Functional Collaboration

• Collaborate with Product Management, Enterprise Applications, Software Engineering, Enterprise Architecture, Security, Service Management, and business leaders to ensure successful delivery of product outcomes.
• Lead cross-functional planning and prioritization activities.
• Foster a culture of innovation, customer focus, and continuous improvement.
• Perform other duties as assigned.

Required Knowledge, Skills, and Abilities

• Demonstrated experience defining and managing enterprise data, analytics, business intelligence, AI, or integration products.
• Strong understanding of modern product management principles and product operating models.
• Experience with enterprise reporting, business intelligence, dashboards, and self-service analytics platforms.
• Understanding of enterprise data governance, data quality, metadata, and master data management concepts.
• Knowledge of AI technologies, generative AI, intelligent automation, and enterprise AI governance.
• Experience defining integration strategies, APIs, and enterprise data exchange capabilities.
• Strong stakeholder management, facilitation, and executive communication skills.
• Ability to translate business needs into product strategies and measurable outcomes.
• Experience using metrics and user feedback to drive product improvements.
• Strong analytical, strategic thinking, and problem-solving capabilities.

Education and Experience Requirements

• Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, Business Administration, or a related field.
• Minimum ten (10) years of progressively responsible experience in product management, enterprise data, analytics, AI, business intelligence, or related disciplines.
• Minimum five (5) years leading cross-functional product initiatives or product teams.
• Demonstrated experience delivering enterprise-scale data, analytics, AI, or reporting capabilities.
• MBA or advanced degree preferred.

Preferred Certifications

• Certified Scrum Product Owner (CSPO), Professional Scrum Product Owner (PSPO), or equivalent.
• Microsoft Fabric, Power BI, Tableau, or equivalent analytics certifications.
• DAMA Certified Data Management Professional (CDMP).
• AI or machine learning certifications from recognized cloud providers or technology vendors.

Success Measures

• Adoption and business value of enterprise data, analytics, AI, and reporting products.
• Improvement in organizational data quality and reporting capabilities.
• Successful delivery of AI-enabled business capabilities.
• Increased use of self-service analytics and reporting.
• Improved integration and interoperability across enterprise platforms.
• Stakeholder satisfaction and measurable business outcomes.
• Delivery of product roadmaps aligned with organizational priorities.

Language

• Fluency, both written and spoken, in English is required.
• ICANN is a global organization that values diversity; preference will be given to candidates with demonstrated skills in additional languages besides English.

Working Conditions & Physical Requirements

• Work is performed in a normal office environment with limited privacy and some exposure to background noise.
• While performing the duties of this job, the employee is frequently required to stand and walk. The employee regularly is required to sit. The employee is frequently required to talk or hear; use hands and arms to reach, handle or feel. Specific vision abilities required by this job include close vision, color vision, and ability to adjust focus.
• The employee may occasionally lift and/or move up to 25 pounds.

Targeted Base Salary Low:

Targeted Base Salary High:

Note: The salary range provided here is a general estimation for the position at the time of posting based on the primary location. Salary ranges vary based upon geographic regions and countries. Final compensation packages take into consideration of a variety of factors including but not limited to a candidate’s location, work experience, knowledge, skills and other compensable factors.