• Evaluate and analyze data from legacy systems and disparate sources to assess quality, completeness, and consistency • Develop and apply practical approaches to profile complex datasets, including structured and semi-structured data • Identify data gaps, anomalies, and structural issues that may impact reporting, analytics, or system migration • Recommend data quality improvements and remediation actions that are aligned to both current-state use and future-state system needs • Support data readiness efforts for modernization and system replacement, including migration considerations • Collaborate with stakeholders to validate findings and align on data priorities and remediation strategies • Document data issues, patterns, and recommendations in a clear, actionable format • Partner with program and technical teams to improve data usability for reporting and analytics

• Champion Iterative Value: Work closely with data engineers and stakeholders to prioritize, scope, and deliver impactful data and analytics deliverables using agile, outcome-oriented methods. • Lead Discovery: Regularly engage with a diverse group of stakeholders (internal and external) to surface, clarify, and prioritize their data needs. • Craft Requirements: Translate business questions and stakeholder needs into clear, actionable requirements and well-defined deliverables (analytics, metrics, dashboards, pipelines). • Drive Execution: Collaborate with data and engineering teams to develop, launch, and refine analytics deliverables in short, learn-and-adapt cycles. • Deliver Results: Manage competing priorities, set expectations, communicate status, and iterate quickly based on feedback and evolving needs. • Measure Impact: Devise, research, and define the metrics and formulae that help Heartbeat and its partners measure success - clinical, operational, financial, and beyond. • Hands-On Contribution: Roll up your sleeves with SQL to shape dashboards, debug data pipelines, and ensure analytic quality. • Monitor & Respond: Help monitor critical data pipelines, respond quickly to disruptions, and ensure data quality, reliability, and trust.

• Analyze performance data across various marketing channels, including Paid Media, CRM, Email Marketing, and Customer Engagement Programs. • Prepare recurring reporting packages and consolidate data into actionable summaries. • Support the development of client recommendations and optimization strategies. • Perform quality assurance checks across reports and datasets. • Collaborate with Strategy, Client Services, Media, and Analytics teams to deliver insights. • Use AI tools responsibly to improve efficiency and reporting processes.

• Gather client metrics across the SIS business to be used in evaluating our impact and business strategy. • Identify, clean, merge, and filter datasets from multiple sources to generate high-quality cross-functional datasets. • Develop strategic data visualizations. • Create, deliver, and manage a client survey system to calculate key metrics to improve the delivery of solutions. • Develop scalable data systems using advanced tools such as coding programs and AI. • Support software development and maintenance. • Support data management and analysis in CRM platforms. • Translate analytic insights into clear business actions to ensure SIS makes well-informed decisions based on empirical evidence.