Manager, MCE Analytics

Sits within the Membership and Customer Excellence (MCE) Division, which delivers world-class experiences and deepens engagement across all customer segments, overseeing clubhouses, racecourses and Off-Course Betting Branches while leading the Club's customer experience strategy across digital and physical touchpoints. The Division also manages data strategy and governance to build a unified view of customers, enabling more personalised and impactful interactions. The position is responsible for orchestrating statistical modelling, internal data analysis and full-scale research and analytics projects that inform business, industry, competitor, product, channel and member behaviour monitoring at portfolio level, working in consultative partnership with senior management, internal stakeholders and external agencies.

• Orchestrate analyses, including statistical modelling and internal data analyses, that help the business monitor the business environment, industry trends, the competitive landscape, product and channel performance, and shifts in member behaviour at portfolio level.
• Provide professional advice and foster consultative partnership relationships with internal stakeholders.
• Proactively manage changes in project scope, identify potential issues and conflicts, and devise resolutions and contingency plans.
• Develop full-scale research and analytical project plans and associated project documents.
• Define research and analytics project scope, goals and deliverables that support business goals and KPI monitoring in collaboration with senior management and stakeholders.
• Manage agencies to deliver quality data and reports with actionable insights for business use.
• Develop best practices and tools for project execution and management.

• Minimum 8 years of experience in data analytics, statistical analysis, AI applications, data science or similar fields.
• Strong experience in dashboarding and data visualisation (e.g., Tableau, Power BI) to support decision making.
• Python for analytics and modelling, including common libraries such as pandas, numpy and scikit-learn.
• SQL for querying large operational and customer datasets and building analytical data structures.
• Experience with AI-assisted tools and platforms, including Microsoft Copilot Studio, for prototyping conversational agents and workflow automation.
• Familiarity with data pipeline orchestration and privacy-aware processing (hashing, masking, secure handling).

• Exposure to machine learning techniques, customer or user experience analytics, and operational forecasting is preferred.

• Competitive salary and benefits package.
• Dynamic working environment.
• Development opportunities.