Jobs at Verana Health

Conduct observational real-world data studies for life sciences clients using EHR and claims data. Develop statistical analysis plans, execute analyses, create research algorithms, and contribute to publications. Lead client calls as the scientific authority, translate clinical questions into analytics requirements, and collaborate with commercial, medical, product, engineering, and sales teams. Apply biostatistical and epidemiological methods across therapeutic areas including oncology, ophthalmology, and urology.

Design, develop, and maintain scalable APIs, backend services, user interfaces, and business applications. The role includes cloud infrastructure and CI/CD optimization using AWS, Docker, and Kubernetes; application security; testing; observability; Agile collaboration; and mentoring junior engineers. The engineer will independently drive solutions from design through production while applying modern system design, database, microservices, and AI-assisted development practices.

Lead and manage a team developing and operationalizing machine learning systems for structured and unstructured clinical data (EHR, text, imaging). Define technical strategy, oversee model lifecycle management, fine-tune and deploy foundation models, ensure data quality and model governance, partner cross-functionally, and mentor ML scientists and technical leaders.

Lead development and implementation of scalable analytic workflows on messy EHR data to generate real-world evidence. Design and execute retrospective studies, develop algorithms, establish reproducible Git-based practices, collaborate cross-functionally, present findings, and drive methodological and infrastructure improvements to support life sciences commercial projects.

Lead vision, strategy, and execution for autonomous AI agents and multi-agent workflows for life sciences and provider-facing use cases. Translate user needs into technical requirements, define safety guardrails and UI, partner with engineering/data science/legal/security to move agents into production, set product metrics (accuracy, task completion, cost, trust), and represent the product at partner sites and conferences.