Director - Customer AI & Analytics

Overview

Customer Data Strategy & Transformation

• Define and lead Qiddiya s enterprise Customer Data & AI strategy aligned with business growth, visitor experience, and digital transformation objectives.
• Establish the long-term roadmap for customer data products, customer intelligence, AI enablement, and monetization opportunities.
• Build a unified customer data vision across ticketing, CRM, loyalty, mobile applications, digital platforms, attractions, hospitality, retail, mobility, and operational ecosystems.
• Drive enterprise adoption of customer-centric decision-making and data-driven engagement models.

Customer 360 & Data Products

• Lead the development and evolution of enterprise Customer 360 capabilities and customer master data architecture.
• Define and oversee customer data products enabling:
• Visitor insights and segmentation
• Personalization and recommendation engines
• Customer lifetime value analysis
• Revenue and conversion analytics
• Loyalty and engagement intelligence
• Cross-channel customer journey analytics
• Real-time audience intelligence
• Predictive behavior modeling
• Partner with Data Engineering and Platform teams to ensure scalable and secure customer data pipelines and architectures.
• Enable self-service analytics and business consumption of customer intelligence products.

AI & Advanced Analytics

• Lead AI initiatives focused on customer engagement, personalization, operational intelligence, and business optimization.
• Identify and drive high-value AI use cases including:
• AI-powered personalization
• Recommendation engines
• Conversational AI and intelligent assistants
• Customer sentiment analysis
• Dynamic audience targeting
• Predictive analytics
• AI-driven campaign optimization
• Generative AI use cases for customer engagement
• Collaborate with BI, Data Science, MLOps, and Emerging Technology teams to operationalize AI solutions.
• Establish AI governance principles aligned with enterprise standards and responsible AI practices.

Leadership & Organizational Development

• Build and lead a high-performing Customer Data & AI function within the Data Office.
• Mentor multidisciplinary teams across analytics, AI, customer intelligence, and data product domains.
• Foster a culture of innovation, experimentation, agility, and business value realization.
• Support enterprise data literacy and AI adoption initiatives.