Casino Analytics Officer

The Casino Analytics Officer supervises data-driven initiatives that improve casino performance, player engagement, and profitability. Collaborating with teams across Gaming Operations, Marketing, and Finance, the Casino Analytics Officer transforms complex data into actionable insights that guide daily operations and tactical decisions. This role oversees the analytics team's workflow, ensures data accuracy, and contributes to the development of reporting tools and dashboards. The Casino Analytics Officer also supports strategic analytics projects and fosters a data-informed culture throughout the organization.

Essential Functions

• Define and execute the casino's analytics strategy and roadmap across key areas such as player lifetime value (LTV) modeling, game performance, floor optimization, and promotional effectiveness.
• Oversee the preparation, accuracy, and timeliness of all standardized and ad-hoc reports, including weekly and monthly performance dashboards, KPI reports, and ROI analyses.
• Ensure that data-driven insights are effectively translated into actionable recommendations that improve profitability, player engagement, and operational efficiency.
• Develop and maintain advanced dashboards and business intelligence (BI) tools to support real-time decision-making across departments.
• Drive the creation and implementation of predictive and statistical models (e.g., churn prediction, player segmentation, forecasting) to identify high-value opportunities.
• Establish and enforce best practices in data governance, data quality management, and analytical methodology.
• Collaborate with Data Engineering teams to ensure data integrity, accuracy, and accessibility across all gaming, marketing, and operations data systems.
• Review and validate data sources and reports to guarantee alignment with internal standards and regulatory requirements.
• Maintain up-to-date documentation of analytical processes, methodologies, and data definitions to support transparency and reproducibility.
• Identify emerging trends, technologies, and regulatory developments in gaming analytics and recommend updates to tools, processes, or methodologies.
• Support compliance with gaming regulations, internal audit standards, and data privacy policies.
• Develop and implement continuous improvement initiatives to enhance the efficiency and accuracy of analytics workflows.
• Ensure the analytics team operates within the highest standards of confidentiality and professional ethics regarding player and business data.
• Regularly monitor and assess the accuracy and reliability of key metrics used by senior management for strategic decision-making.
• Provide critical data insights during strategic planning, financial forecasting, and operational reviews.
• Ensure consistency and alignment of reporting methodologies across all departments.
• Prepare weekly, monthly, and quarterly analytics summaries and performance reviews for senior management.
• Compile special reports and presentations for executive meetings, business reviews, and regulatory audits.
• Maintain a repository of casino analytics outputs for reference, benchmarking, and long-term performance tracking.
• Perform regular system audits to ensure analytics tools and databases are up-to-date and performing optimally.
• Recommend process automation and digital transformation initiatives to enhance the speed and precision of analytics operations.
• Ensure full adherence to corporate data handling, cybersecurity, and compliance standards.

Job Requirements

Education and Experience

• Bachelor's Degree in Business, Marketing, Finance, Data Science, Statistics, or a related quantitative field.
• 2 to 3 years of progressive experience in casino analytics, gaming data science, or a related business intelligence environment.
• At least a year of experience leading or mentoring a team of analysts.
• Proven proficiency in advanced SQL for data extraction and manipulation.
• Strong working knowledge of BI and visualization tools (e.g., Tableau, Power BI, Looker).
• Demonstrated experience with predictive modeling, statistical analysis, or experimental design (A/B testing).