• Own the analytical narrative for your Operating Group (OG). Be the strategic thought partner across cross-functional teams (PMs, engineers, marketing, finance). You understand the roadmaps and users, and you set the agenda for the highest-leverage questions the OG should be asking. • Tell stories that move teams to act. You'll present to leadership and working teams with clear narratives and a point of view. A great insight that nobody acts on is a failed insight. • Establish causality with the right tools for the situation, including A/B testing, analytics, and causal inference. You work with engineering to implement event instrumentation and with Product to translate insights into action. • Define metrics strategies that measure what matters. Work backward from how users experience the product to develop and implement the measurement frameworks for your OG, in a complex ecosystem with multi-user engagement and many ways to interact with the product. • Build explanations on top of measurement, always grounding analysis in the reality that users are people with motivations and context the data alone won't tell you. • Shape the AI-native analytics stack. Lead evaluation and adoption of new tools, agent workflows, and practices that enable self-serve across the OG and move the team from reactive to proactive to autonomous. • Mentor senior ICs on causal thinking, experimental rigor, and AI-leveraged workflows. Raise the ceiling of the craft.

• Be the strategic thought partner for cross-functional teams (PMs, engineers, marketing, finance).You understand the roadmaps and users, and you notice the gap between what the data shows and what the team assumes. • Tell stories that move teams to act. You'll present to leadership and working teams with clear narratives and a point of view. A great insight that nobody acts on is a failed insight. • Establish causality with the right tools for the situation, including A/B testing, analytics, and causal inference. You work with engineering to implement event instrumentation and with Product to translate insights into action. • Work backward from an understanding of how users experience our product to develop and implement metrics strategies that measure what matters to our users and our business. This enables a deep understanding of our users and their motivation, in a complex ecosystem with multi-user engagement and many ways to interact with our product. • Build explanations on top of measurement, always grounding analysis in the reality that users are people with motivations and context the data alone won't tell you. • Use AI to multiply your impact. You'll use coding agents and automated analysis daily, and help shape what our AI-native analytics stack looks like, contributing to how we move from reactive to proactive to autonomous.

• Conduct age-appropriate history and virtual exams • Evaluate, diagnose, and treat a broad range of conditions across the lifespan • Order and interpret diagnostic tests as needed • Develop and document treatment plans in a timely, accurate manner • Manage acute, chronic, and mental health conditions for pediatric and adult patients • Request consultation or referral with other health care providers when appropriate • Counsel and educate patients and families on treatment plans • Maintain current knowledge of clinical best practices and evidence-based care • Provide cross-coverage for tasks such as reviewing lab results • Offer scheduling flexibility, including evenings and weekends

• Manage and maintain the 'Golden Record' for core data domains (Customer and Product), including resolving data conflicts and duplicates. • Manage data hierarchies, relationships, and cross-system mapping. • Oversee the matching and merging process to improve consolidation of data. • Establish, measure and monitor Data Quality KPIs (Accuracy, Completeness, Timeliness, Consistency) • Perform root-cause analysis on data discrepancies and lead remediation efforts. • Design and implement automated data profiling, validation and cleansing processes. • Support the development of data governance standards, policies, and business rules. • Document data lineage, business glossaries, and data dictionaries. • Facilitate data stewardship activities across business units