• Collaborate with Product Managers to analyze game and monetization data, transforming findings into actionable metrics, insights, and recommendations. • Engage with various stakeholders to define business needs and translate them into precise analytical questions and relevant key metrics. • Design and build efficient, well-structured data models to generate scalable metrics, supporting various tools and processes used for data-informed decision-making. • Conduct in-depth exploratory analysis using analytical tools or efficient SQL queries. • Identify significant trends, anomalies, and opportunities by analyzing data across millions of players.

• Own the data architecture, data mapping and reporting to support Growth Marketing needs for campaign and channel insights • Deliver key performance insights to support the development of member marketing campaigns across email, direct mail, digital, and client-led channels. • Own data tagging, test sizing and statistical analysis for A/B and multivariate campaign and creative tests • Develop and support well-designed Tableau dashboards (or similar BI tools) • Work closely with various data teams to improve data quality and standardize reporting • Define operational processes and support system enhancements that drive analytics and reporting support at scale • Collaborate across multiple teams including analytics, data science, data engineering and architecture, clinical, and product • Explore and integrate applications of AI into product analytics use cases

• Serve as a technical expert and end-to-end owner on marketing data sources, analytics infrastructure, data models, and analysis and measurement methodologies. • Build, maintain, and interpret acquisition measurement frameworks, including multi-touch attribution, Markov Chain / advanced attribution models, and other channel performance metrics. • Design, implement, and analyze A/B tests and incrementality experiments for product features, marketing campaigns, and UX optimizations. • Evaluate ROI across paid and organic acquisition channels and refine performance metrics over time. • Develop, maintain, and scale in-house multi-touch attribution (MTA) models and media mix models (MMM) • Identify key audience segments within our customer base and across our verticals of care using metrics such as LTV, cross sell %, etc • Lead the development and maintenance of DBT data models and orchestrations, ensuring accuracy, modularity, and performance optimization • Create automated, self-serve dashboards and reporting solutions that empower stakeholders to explore key metrics • Collaborate with Product, Marketing, Finance, and Engineering to translate business questions into analytical tasks, interpreting results for both technical and non-technical audiences.

- Develops moderately complex value-based analytics solutions for quality, business process functionality, or other strategic/data/analytic initiatives of moderate complexity - Collaborates with cross-functional teams to identify and establish analytics requirements - Creates detailed documentation and business plans that address stakeholder needs - Liaises between IT and Product Management for data solutions - Develops and implements moderately complex enterprise-wide data integration strategies that utilize various data marts and data warehouse applications to enhance reporting - Continuously works to improve data platforms, dashboards, and reports to meet emerging and changing business demands and guidelines - Consults with limited guidance from Principal on UAT, technical specifications, strategic planning, contract design, technical support, testing updates, and trainings - Uses intermediate understanding of data elements, structures, standards typically involved in financial services transactions, reporting, and cloud-based data storage/sharing to adopt and apply standards in a way that satisfies and balances regulatory and compliance requirements with business needs - Manages data from multiple sources and uses project management skills to complete moderately complex projects with minimal coaching and guidance - Transmits data and proactively works to ensure data quality - Troubleshoots data issues and devises creative and effective ways to avoid or mitigate issues