9amHealth - VP of Data

• This isn’t a heads-down execution role or a narrow analytics role. We want someone who can think strategically about the member journey, clinical operations, business economics, and the operational implications of data and ML decisions — and who can lead a multi-discipline team (data engineers, analysts, data scientists, ML engineers) to do the same. • What the Day-to-Day Looks Like • Day to day, the role is highly collaborative and fast-moving. • You’d work closely with: • The CEO and executive team on company strategy, metrics, and reporting • Data engineers, analytics engineers, analysts, data scientists, and ML engineers across the data org • Product and Engineering leadership on instrumentation, experimentation, and ML in production • Clinical leadership, care coordinators, and coaches on outcomes, quality measurement, and model evaluation • Growth, marketing, finance, and operations leaders on the metrics that run the business • Compliance and security partners on PHI handling, HIPAA, audit, and access controls • A typical week could involve: • Setting and communicating data vision, strategy, and roadmap across data engineering, analytics, and DS/ML • Reviewing the core company metrics — engagement, retention, clinical outcomes, unit economics — and shaping what gets prioritized • Partnering with Product and Clinical on experiment design, sample sizing, and reading results responsibly • Coaching and developing managers and ICs across the data org • Making tradeoff decisions between platform investment, analytics throughput, and ML/AI bets • Working with engineering leadership on data architecture, real-time vs. batch needs, and model deployment • Reviewing ML model performance, drift, and clinical safety considerations before anything ships into care workflows • Representing data in board conversations, investor updates, and cross-functional planning • We move quickly, so there’s an expectation that the VP can drive clarity and decisions even when the brief is incomplete, the data is messy, and the model evaluation isn’t clean. • Team / Collaboration Structure • The role reports directly to the CEO and is a member of the executive team. The VP of Data will own and grow the data organization end-to-end: data engineering and platform, analytics engineering and BI, data science, and applied ML / AI. • One thing worth highlighting is how cross-functional the environment is. Data isn’t a service team that fulfills tickets — it’s embedded in how product, clinical, and operations decisions get made. Adding a new metric, surfacing a new lab value, or shipping an ML-driven recommendation can meaningfully change what care teams do day to day, so we’re looking for a leader who naturally thinks in systems rather than just dashboards or models in isolation. • The engineering and product organization is distributed between San Diego and Vienna, plus remote teammates across the US. The VP will need to be effective leading a distributed team and comfortable building rituals and writing artifacts that keep a remote, multi-time-zone org aligned. • The strongest candidates are people who have owned a full data function end-to-end at scale and can speak clearly about strategy, outcomes, tradeoffs, and team building across data engineering, analytics, and ML. • We’re especially interested in data leaders who: • Have led data orgs through meaningful scale (early growth through multi-team) • Have built and matured data platforms — ingestion, warehousing, modeling, governance — without over-engineering • Have shipped ML or applied AI into a real product, not just into a notebook • Have operated in ambiguity and built clarity from it (definitions, ownership, metric trees, source of truth) • Move quickly and independently and push teams to do the same • Are comfortable making decisions with imperfect data • Have strong product and business instincts in addition to technical depth • Understand experimentation, causal inference, and the limits of A/B testing in healthcare contexts • Have worked with PHI / HIPAA and understand the compliance, privacy, and security implications of data work in healthcare • Can defend decisions clearly to the executive team, the board, and the broader org • Have hired, coached, and leveled up data engineers, analytics engineers, analysts, data scientists, and ML engineers • We also want someone who’s genuinely fluent with modern AI-assisted tooling. That doesn’t just mean having tried ChatGPT once or twice. We want a leader who actively uses tools like Cursor, Claude, v0, or Lovable in their own workflow, who has hands-on opinions about where LLMs and agents accelerate data and analytics work, where they’re still risky in a clinical setting, and who can set the standard for how the broader data and engineering org adopts AI responsibly. • Healthcare or regulated-industry experience is a strong plus but not required if the data and ML leadership chops are strong. • The VP of Data doesn’t need to be hands-on in the production codebase, but should be technically conversant and able to make credible architecture and platform decisions. Our current stack: • Backend: AWS, MySQL, Java/Spring Boot, some Python, JSON/REST APIs • Frontend: TypeScript, React, Capacitor/Ionic • Tools / Systems Worth Mentioning • We work in a modern, collaborative product environment. The tools we run on day to day: • Google Workspace • AI-assisted tooling that comes up frequently in product, engineering, and data workflows: Cursor, Claude, v0, Lovable, and rapid prototyping environments. We’re much more interested in adaptability, systems thinking, and judgment than whether someone has used one exact tool for years.