• Define, implement, and maintain product metrics and KPIs across adoption, usage, funnels, engagement, and clinical impact. • Build and maintain dashboards and reporting in tools such as Looker, Mode, or similar, surfacing timely insights to product and clinical stakeholders. • Design, run, and analyze A/B tests, multivariate experiments, and cohort analyses to validate feature impact and inform product strategy. • Develop statistical models (e.g., regression, survival analysis, causal inference) to quantify the relationship between clinician behavior and clinical or business outcomes. • Instrument features using product analytics tools (e.g., Pendo, Mixpanel, Amplitude), owning event schema design, funnel tracking, and behavioral segmentation. • Query and transform data from cloud data warehouses (BigQuery, Snowflake, Redshift) using advanced SQL, and supplement with Python as needed. • Partner with data engineering to validate data pipelines, ensure data quality, and maintain consistent and trustworthy metric definitions. • Translate quantitative findings into clear recommendations that influence product direction and roadmap decisions. • Monitor post-launch performance to identify adoption gaps, usability issues, or opportunities for iterative improvement. • Support deep-dive analyses on provider workflows, care gap closure, chronic disease management, and population-level clinical metrics. • Assist in occasional clinical validation or root-cause investigations, including anomalies in clinical outputs or edge-case usage patterns.