Data Scientist, Global Gaming

The Data Scientist will support Casino Operations Analytics Team by applying machine learning and advanced analytics to improve operational decision-making and guest experience.

Key responsibilities include:

Translating operational business questions into analytical and machine learning solutions. Owning projects end-to-end: data exploration, cleaning, feature engineering, modeling, validation, and deployment. Building predictive models for use cases such as:
Optimizing product offerings and mix. Analyzing guest play behavior and segmentation. Predicting retention and lifetime value. Demand forecasting and operational planning. Supporting experimentation and incentive effectiveness analysis. Ensuring data integrity and model reliability. Communicating insights clearly to both technical and business stakeholders. Proactively identifying opportunities to improve analytical capabilities within the team.

This role offers growth potential, including the opportunity to help expand and shape the team's data science capabilities over time.

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* Essential Functions:

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* + Develop and Implement Predictive & Analytical Models - Design, build, validate, and refine machine learning and statistical models to address operational business problems such as demand forecasting, guest behavior analysis, and product optimization.

+ Data Exploration, Cleaning, and Validation - Perform in-depth data exploration, quality assessment, cleaning, transformation, and feature engineering to ensure reliable inputs for modeling and analysis

+ Translate Business Requirements into Analytical Solutions - Collaborate with operations and analytics stakeholders to define problem statements, success metrics, and analytical approaches aligned with business objectives.

+ Deploy and Maintain Production-Ready Models - Support deployment of models into operational environments, monitor performance, and implement improvements to ensure accuracy and reliability over time.

+ Conduct Experimentation and Performance Analysis - Design and evaluate experiments (A/B testing) and assess effectiveness of operational initiatives, incentives, and product strategies.

+ Demand Forecasting and Operational Planning Support - Develop forecasting models and scenario analyses to support staffing, capacity planning, and operational decision-making.

+ Communicate Insights and Recommendations - Prepare clear summaries, visualizations, and presentations to communicate findings to both technical and non-technical stakeholders.

+ Proactively Identify Opportunities for Analytical Improvement - Identify areas where advanced analytics or machine learning can enhance operational efficiency, guest engagement, or product performance.

Knowledge, Skills & Abilities:

+ Scope:
Applies advanced analytics and machine learning to optimize casino operations, enhance guest experience, and support data‑driven decision‑making across forecasting, segmentation, experimentation, and product strategy.

+ Problem solving:
Translates complex operational questions into analytical frameworks, builds and validates predictive models, and resolves data quality and model‑performance issues across multiple systems and stakeholders.

+ Impact:
Drives measurable improvements in operational efficiency, guest engagement, and revenue outcomes by delivering accurate forecasts, actionable insights, and reliable production‑ready models.

+ Leadership:
Leads end‑to‑end analytical initiatives, elevates team capabilities through proactive innovation, and communicates technical findings clearly to influence decisions across both technical and business partners.

Qualifications:

+ Bachelor's Degree Data Science, Statistics, Computer Science, Mathematics, Engineering, Economics, or related quantitative field required. Masters Degree Data Science, Statistics, Computer Science, Mathematics, Engineering, Economics, or related quantitative field preferred.

+ Minimum 4 years of hands-on experience in data science or applied machine learning. Experience building predictive models using real-world, large-scale structured data. Experience delivering models into production or operational environments. Experience working…