Manager Data, Insights, Analytics & Reporting

About This Role

Key Responsibilities

1. Data Strategy, Architecture & Governance

• Define and own WESTAY’s enterprise data strategy, architecture, and roadmap, aligned with commercial, brand, product, and operational priorities
• Lead the design and evolution of WESTAY’s first-party data layer across web, app, CRM, booking, and operational systems
• Establish data governance, taxonomy, definitions, lineage, and quality standards across all functions
• Ensure compliance with GDPR, CCPA, and relevant global privacy and data protection regulations
• Partner with engineering and product to embed data-by-design principles into every digital and operational touchpoint

2. Analytics Integration, Tagging & Tracking Infrastructure

• Lead end-to-end deployment, maintenance, and QA of analytics and tracking infrastructure including:
• Tag management systems (GTM, server-side tagging)
• Web and app analytics (GA4, Adobe Analytics, Mixpanel, Amplitude or equivalents)
• Conversion APIs and offline conversion uploads
• Cookieless and consent-aware measurement frameworks
• Own the data layer specification, event taxonomy, and parameter governance across all digital properties
• Ensure tracking accuracy, redundancy, and resilience across paid media, organic, CRM, and product analytics
• Manage analytics vendors, technology partners, and implementation agencies with clear KPIs and accountability

3. Business Intelligence, Reporting & Visualization

• Build and own WESTAY’s enterprise BI and reporting ecosystem, delivering trustworthy, self-serve insight at every level of the business
• Design executive, commercial, brand, product, and operational dashboards using modern BI stacks (Looker, Tableau, Power BI, Mode or equivalents)
• Establish a single source of truth for KPIs across revenue, bookings, marketing performance, customer, and operations
• Define reporting cadences, SLAs, and narrative briefings for the leadership team
• Champion data literacy, visualization standards, and self-serve analytics across the organization

4. Data Science, Advanced Analytics & Predictive Modeling

• Build and lead WESTAY’s data science capability, applying statistical, machine learning, and AI techniques to commercial and customer challenges
• Develop predictive and prescriptive models including:
• Demand forecasting and dynamic pricing inputs
• Customer lifetime value and churn prediction
• Propensity, segmentation, and next-best-action models
• Marketing mix and incrementality modeling
• Design and run experimentation programmes (A/B, multivariate, causal inference) across product, marketing, and operations
• Operationalize models into decisioning, personalization, and CRM activation in partnership with engineering and martech

5. Customer, Market & Industry Insights

• Lead WESTAY’s customer and market insights agenda, fusing first-party behavioural data, qualitative research, and third-party industry intelligence
• Build a continuous intelligence engine covering competitive benchmarking, destination trends, traveller sentiment, and luxury lifestyle signals
• Surface trends, white-space opportunities, and demand shifts across hospitality, aviation, yachting, and adjacent luxury categories
• Translate data into clear, narrative-led insights that inform strategy, product, brand positioning, and commercial planning
• Partner with PR, brand, and partnerships teams to shape data-driven thought leadership and proprietary industry reports

6. Data Platform, Engineering Partnership & AI Enablement

• Partner with engineering and product to design and scale the modern data platform — data warehouse / lakehouse, ELT pipelines, reverse ETL, CDP, and ML infrastructure
• Champion the adoption of AI and generative AI tooling for analytics acceleration, internal copilots, and insight automation
• Build and lead a high-performing team across analytics engineering, BI, data science, and insights, while orchestrating external specialists where appropriate
• Establish operating rituals — backlog management, prioritisation frameworks, and stakeholder partnership models — that turn data into a strategic asset
• Define and manage the data and analytics budget with clear ROI and business impact tracking