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Lead product marketing strategy for Omada Health’s cardiometabolic portfolio, including diabetes, hypertension, weight management, cholesterol, and GLP-1 programs. Own positioning, competitive differentiation, packaging, pricing, go-to-market planning, product launches, sales enablement, and marketing content. Partner with product, clinical, commercial, and thought leadership teams while leading, mentoring, and developing a team of 2–3 product marketers.

Design and build web applications supporting member enrollment, including eligibility verification, benefit matching, signup, and activation. Write tested, maintainable code; design scalable APIs; participate in architecture and technical decisions; use AI coding agents throughout development; collaborate with Product and Marketing; monitor system reliability; and participate in on-call support for the enrollment pipeline.

Own the end-to-end B2B2C enrollment funnel for Customer Success, including reporting, data modeling, funnel metrics, dashboards, attribution, and operating cadences. Identify data and process gaps, deliver decision-ready recommendations, lead stakeholder reviews, and drive cross-functional improvements across Operations, Customer Success, Marketing, and Engineering. Lead annual Customer Success planning for capacity, territories, quotas, incentives, roadmaps, and targeting.

As Chief Revenue Officer, lead Omada Health's commercial strategy to drive growth, market access, and integration of AI in operations, ensuring sustainable success across healthcare channels.

Lead backend-focused engineering to design and ship member- and care team-facing experiences. Own architecture end-to-end, set technical direction and quality standards, mentor engineers, and deliver scalable, secure APIs with CI/CD, cloud deployments, and GenAI/LLM-informed workflows.

Lead and mature Omada's enterprise privacy program, manage HIPAA compliance and incident response, embed privacy-by-design across products, conduct privacy risk assessments and vendor due diligence, advise on consumer privacy and AI governance, support interoperability/HIE participation, and deliver privacy training and guidance across the business.

Design, build, and operate scalable data and AI platform capabilities. Create reusable abstractions, templates, and services for data pipelines and products. Integrate Generative AI for discovery and automation, ensure data quality, lineage, observability, security, and support cross-functional analytics and applied-AI teams.

Design, build, and maintain scalable, secure data architectures, models, and ETL pipelines. Integrate diverse data sources, optimize performance and data quality, implement governance, monitor production SLAs, and collaborate with data scientists, analysts, and product teams. Provide technical leadership, documentation, and training to improve engineering practices across the organization.

Lead research and development of longitudinal health trajectory models and next-best-action decision algorithms. Translate member data into deployable, clinically meaningful models, set evaluation standards, mentor scientists, and collaborate with product, engineering, and clinical teams to productionize and monitor ML solutions that optimize interventions and health outcomes.

Lead design and implementation of scalable backend systems that ingest, process, and serve high-volume health data. Own projects end-to-end, drive integrations with third-party APIs, improve data reliability and observability, mentor engineers, and partner with product, clinical, and data teams to deliver clinically meaningful insights.