Senior Product Owner - Data Products & AI

Key Responsibilities

Data Product Management & Delivery

• Drive execution of the data product roadmap aligned with business priorities.
• Partner with business, analytics, and engineering teams to deliver trusted data products and insights.
• Manage product backlogs, prioritization, release planning, and delivery governance.
• Track and measure business value generated through data products.

AI & Innovation Programs

• Lead execution of AI/ML initiatives and innovation programs.
• Drive use cases across personalization, customer engagement, digital commerce, compliance, and automation.
• Coordinate pilots, experiments, PoCs, and business testing activities.
• Track adoption and business outcomes of AI initiatives and recommend enhancements.

Analytics & Experimentation

• Implement experimentation frameworks including A/B testing and product validation approaches.
• Analyze product performance and generate actionable business insights.
• Identify growth opportunities through data and customer behavior analysis.
• Establish reporting mechanisms to measure product and business impact.

Digital Analytics & Measurement

• Drive digital analytics implementation across web and mobile platforms.
• Ensure tracking and measurement frameworks are effectively governed and maintained.
• Partner with engineering teams to improve data capture and reporting accuracy.
• Develop dashboards and KPI reporting to support data-driven decision-making.

Stakeholder & Program Management

• Act as the key liaison between business, analytics, data engineering, and technology teams.
• Manage timelines, dependencies, risks, and communication across projects.

Desired Profile

• 8+ years of experience in Data Analytics, Product Management, Digital Transformation, Business Analytics, or AI Program Management.
• Strong understanding of data products, analytics platforms, BI tools, and AI/ML use cases.
• Experience managing cross-functional teams and influencing senior stakeholders.
• Exposure to experimentation frameworks, customer analytics, and product performance measurement.
• Familiarity with cloud data platforms, data governance, and digital analytics ecosystems.