Director - Customer AI & Analytics

AI in this role

ml-opsai-safety

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.

How we rate this

Director - Customer AI & Analytics at Qiddiya Investment Company rates 72 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ML OpsAI Safety

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
How do you think about the risk of an AI system in this kind of role failing silently?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: ML Ops and AI Safety. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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