VP of Data

About

9amHealth is an AI-enabled virtual specialty care platform focusing on managing high-cost chronic conditions at scale. The company partners with employers, health plans, and pharmacy benefit managers to deliver comprehensive, cost-effective medical care for individuals living with obesity, diabetes, hypertension, and dyslipidemia. Members gain access to specialized clinicians, at-home lab testing, prescription medications, and lifestyle support.

Responsibilities

• Own the entire data function, including data engineering and platform, analytics and BI, and data science/ML/AI.
• Powers member app, internal EMR, operational tooling, and AI-assisted workflows.
• Set vision, strategy, and roadmap for data org, build and grow the team, and partner with executive team to translate strategy into data, analytics, and ML roadmap.
• Collaborate with CEO and executive team on company strategy, metrics, and reporting.
• Work with Product and Engineering leadership on instrumentation, experimentation, and ML in production.
• Partner with Clinical leadership, care coordinators, and coaches on outcomes, quality measurement, and model evaluation.
• Work with Growth, Marketing, Finance, and Operations leaders on metrics that run the business.
• Work with Compliance and Security partners on PHI handling, HIPAA, audit, and access controls.

Qualifications

• Leadership experience in scaling data functions through multiple teams.
• Experience building and maturing data platforms, including ingestion, warehousing, modeling, and governance.
• Experience shipping ML or applied AI into a real product, not just into a notebook.
• Ability to operate in ambiguity and build clarity from it.
• Comfortable making decisions with imperfect data.
• Strong product and business instincts combined with technical depth.
• Experience with experimentation, causal inference, and understanding the limits of A/B testing in healthcare contexts.
• Experience with PHI/HIPAA and understanding the compliance, privacy, and security implications of data work in healthcare.
• Ability to defend decisions clearly to the executive team, the board, and the broader org.
• Hiring, coaching, and leveling up data engineers, analysts, data scientists, and ML engineers.
• Genuine fluency with modern AI-assisted tooling.

What We're Looking For

• Experience owning a full data function end-to-end at scale.
• Clear communication of strategy, outcomes, tradeoffs, and team building across data engineering, analytics, and ML.
• Adaptability, systems thinking, and judgment.
• Effective leadership of a distributed team.

What the Day-to-Day Looks Like

• Setting and communicating data vision, strategy, and roadmap.
• Reviewing core company metrics and shaping priorities.
• Partnering with Product and Clinical on experiment design, sample sizing, and responsible reading of results.
• Coaching and developing managers and ICs.
• Making tradeoff decisions between platform investment, analytics throughput, and ML/AI bets.
• 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.

Team / Collaboration Structure

• Reports directly to the CEO and is a member of the executive team.
• Owns and grows the data organization end-to-end: data engineering and platform, analytics engineering and BI, data science, and applied ML/AI.
• Works in a cross-functional environment where data impacts member journeys, clinical operations, business economics, and operational efficiencies.
• Works with distributed teams across San Diego, Vienna, and remote US.

Coding Stack

• Backend: AWS, MySQL, Java/Spring Boot, some Python, JSON/REST APIs.
• Frontend: TypeScript, React, Capacitor/Ionic.

Tools / Systems

• Apple Mac
• Google Workspace
• Zoom
• Slack
• Confluence
• Jira
• Miro
• Figma
• Mixpanel
• 1Password
• Zendesk
• HubSpot
• Rippling
• AI-assisted tooling: Cursor, Claude, v0, Lovable, and rapid prototyping environments.

Biggest Challenges in the Role

• Balancing speed, ambiguity, and complexity at the leadership level.
• Member clarity, engagement, and clinical outcomes.
• Clinical safety, model evaluation, and operational efficiency.
• Business economics and unit economics.
• Technical constraints, data platform investment, and tech-debt tradeoffs.
• AI-assisted automation versus human care workflows, including when not to automate.
• PHI, HIPAA, and the privacy and security expectations of working with sensitive health data.
• Building structure for a distributed team.

What Makes the Opportunity Interesting

• Ownership and influence over how chronic care is delivered and measured.
• Opportunity to build data, analytics, and ML holistically across member-facing experience, clinical infrastructure, and operational metrics.

What You Can Expect

• Join a collaborative learning mindset and passion for improvement.
• Work with a small, flexible team of people eager to shape technology, infrastructure, and culture.
• Spread across the globe with physical sites in San Diego, California, and Vienna, Austria.
• Comprehensive benefits package including health, dental, and vision insurance, flexible PTO, and work from home options.
• Professional development budget and support for continuing education.
• The opportunity to make a meaningful impact on chronic disease management and patient outcomes.
• A mission-driven culture focused on improving healthcare accessibility and affordability.
• A commitment to diversity and inclusion, welcoming applications from BIPOC, LGBTQ+, people with disabilities, ethnic minorities, and foreign-born residents.