• Serve as a technical expert and end-to-end owner of care experience data, core metrics, and business reporting • Partner closely with Analytics Engineering to build and improve complex data models that unify data across the patient experience lifecycle. • Partner with Care Experience, Clinical, Product, and Engineering teams to define, track, and improve core business and care KPIs • Investigate care performance trends, operational issues, and data anomalies, and turn findings into clear, actionable recommendations • Build, automate, and maintain dashboards and reports that support daily Care operations and long-term planning • Enable and promote self-service analytics, empowering Care stakeholders across various data exploration and reporting initiatives • Design, run, and analyze experiments and pilots (such as A/B tests and process changes) to measure the impact of care and operational initiatives • Present complex analytical findings to a wide range of audiences • Contribute to the evolution of Care Analytics best practices, including metric definitions, reporting standards, and data governance

• Lead high‑impact analytics initiatives from problem framing through delivery; quantify value, design robust analyses, and communicate recommendations to business partners and executives • Partner with business leaders to identify analytics opportunities and deliver actionable insights. Present findings and recommendations to partners and executive leadership in clear, compelling formats • Develop analytics products and solutions using Databricks, modern Business and Artificial Intelligence tools and Agile principles • Implement advanced analytics where applicable, leveraging Python for advanced analytics, automation, and integration with Databricks workflows • Architect and publish trusted Power BI datasets and dashboards (DAX, Power Query, semantic models), establishing standards for usability and adoption • Build performant Databricks workflows (notebooks, jobs, SQL Warehouses) to wrangle large datasets, engineer features, and automate recurring analyses • Develop Python scripts for automation, data wrangling, and integration with Databricks and Azure services • Partner with Data Engineering on Azure data stack components (Data Factory, ADLS, Synapse/Fabric pipelines) for scalable data solutions • Own analysis quality: data validation, experiment/study design, sensitivity checks, and reproducibility (versioning, documentation) • Define and monitor KPIs; create executive scorecards and operational reporting that tie directly to business objectives • Coach/mentor analysts and BI developers; uplift storytelling, statistical thinking, and visualization craftsmanship across the team • Collaborate with Data Governance and Compliance to ensure appropriate use of PHI and adherence to privacy/security controls • Facilitate data stewardship and literacy across the business • Drive adoption of data products to scale data value • Stay current with emerging technologies and recommend enhancements to the analytics stack

• Complete analysis projects with business stakeholders to monitor the health of the business and help the business make data-driven strategic and operational decisions • Develop and own business intelligence dashboards to provide ongoing tracking and insights to business partners • Build and improve advanced analytical models, such as our fit algorithm and inventory forecasting • Collaborate with data engineering to improve data architecture and maintain a robust and accurate data warehouse • Discover ways to use analytics to support team members across the business to yield action through data-driven decision making • Provide user assistance and direction for ad-hoc data reporting

• Partner closely with our Global Capital Markets Business Development and Customer Experience teams • Analyze data from internal and external sources to identify trends, anomalies, and actionable insights • Partner with Business Development to track and improve partner performance and deal outcomes • Collaborate with Customer Experience to identify customer pain points and issue categories • Build dashboards, reports, and visualizations that inform decision-making across teams • Present findings and recommendations to cross-functional stakeholders, including senior leadership • Support CRM data hygiene and ensure partner-facing teams are accurately leveraging systems and tools • Drive measurement and reporting for strategic initiatives aimed at partner success and growth