Top Data & Analytics Jobs

Transforms large-scale datasets into strategic insights, designs and analyzes experiments, builds scalable reporting frameworks and dashboards, and communicates findings to stakeholders. Partners cross-functionally to improve workflows, optimize performance, support strategic initiatives, and drive measurable business outcomes across casino products and markets.

Build predictive models and customer economics analyses that forecast behavior, optimize marketing investments, and support revenue growth. Develop automated tools, dashboards, and repeatable frameworks to communicate customer performance and retention trends. Partner with Marketing, Finance, Data Science, and Data Engineering to translate complex model outputs into actionable business strategies using technologies including Databricks, Airflow, Bitbucket, SQL, and Snowflake.

Build predictive models forecasting customer behavior, analyze retention and gameplay trends, and create automated tools, analyses, and dashboards. Translate model outputs into actionable recommendations that guide marketing investments, promotional strategies, customer valuation, and retention. Partner with Marketing, Finance, Data Science, and Data Engineering teams while using Databricks, Airflow, Bitbucket, SQL, Snowflake, and dashboarding tools to support revenue growth and customer insights.

Analyzes large-scale datasets to generate strategic insights, design and evaluate experiments, identify trends, and improve business performance. Builds scalable reporting frameworks and dashboards, translates complex analyses into compelling narratives, and partners with cross-functional teams to support strategic initiatives and data-driven decisions across casino products and markets.

Monitor and verify real-time college and professional sports data feeds, identify and resolve discrepancies, cross-check information across sources, troubleshoot issues with technical teams, track sports schedules and statistics, and provide feedback to data collection scouts to improve accuracy and performance.

Design, build, and scale real-time and batch data infrastructure and pipelines (Kafka, Databricks, Snowflake) to power analytics, reporting, and AI-powered data experiences. Drive data modeling, governance, observability, and best practices while partnering with cross-functional teams and mentoring engineers.