Director - Customer AI & Analytics

The Director - Customer AI & Analytics will lead the strategy, governance, architecture, and delivery of customer data products, customer intelligence platforms, and AI-driven engagement capabilities across Qiddiya. This role will establish Qiddiya’s customer data foundation and enable advanced personalization, audience intelligence, loyalty analytics, revenue optimization, and AI-powered customer engagement across parks, entertainment venues, digital channels, hospitality, retail, ticketing, mobility, and future city services. The role requires a highly strategic leader with deep expertise in customer data ecosystems, AI enablement, enterprise data platforms, and digital transformation, combined with strong stakeholder management and execution capabilities. The successful candidate will work closely with Digital, Marketing, Commercial, Customer Experience, IT, Operations, Strategy, and Executive Leadership teams to position customer data as a strategic enterprise asset. Key Responsibilities 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. Requirements Required Experience - 12+ years of experience in Data, Analytics, AI, Customer Intelligence, or Digital Transformation domains. - Proven leadership experience in enterprise-scale customer data and AI initiatives. - Strong experience in Customer 360, CDP, CRM analytics, personalization, and customer intelligence ecosystems. - Experience leading large cross-functional programs involving business, technology, and data stakeholders. - Strong understanding of modern cloud data platforms and AI/ML ecosystems. - Experience in key consumer-oriented industries including Entertainment, Hospitality, Theme Parks, and Retail. - Experience managing strategic vendors, implementation partners, and enterprise programs.