Senior Data Scientist, RVO Health

• You are comfortable owning problems end-to-end, shipping fast, and adjusting course when the data or product direction changes. You don't need perfect requirements to get started
• Generative AI & LLMs — experience building applications with LLMs, prompt engineering, RAG pipelines, LangChain, or similar tooling
• Evaluation & Measurement — designing and building pipelines to assess AI/LLM output quality, including automated annotation, human-in-the-loop review, and defining metrics that reflect real health outcomes
• Clinical NLP & Claims Data — extracting structured insights from unstructured clinical text and/or working with medical claims data to understand patient journeys, diagnoses, and treatment patterns
• Search & Retrieval — building systems that help users find relevant health information, including semantic search, dense retrieval, and RAG architectures
• Behavioral modeling — understanding user engagement, retention, and habit formation patterns in the context of health behavior change

Desirable

• We're a growing team made up of a mix of data scientists, machine learning engineers, analytics engineers, data engineers, and product managers. We welcome candidates from different backgrounds and believe that diverse, inclusive teams are better teams
• We're looking for a Data Scientist to join a fast-moving team building ML and AI solutions for consumer health behavior change products. You'll work on problems where your models directly influence real health outcomes for millions of users. We move fast, iterate often, and expect our scientists to thrive in ambiguity
• Design and build evaluation pipelines to measure AI and LLM output quality, including automated annotation frameworks and human-in-the-loop review workflows
• Apply NLP techniques to clinical and claims data to extract structured insights that inform product and health outcomes
• Build and improve search and retrieval systems that connect users to relevant, accurate health information using semantic search and RAG architectures
• Develop and ship generative AI applications — moving rapidly from proof of concept to production
• Partner closely with Product Managers and Engineers to translate ambiguous health problems into concrete, measurable data science solutions
• Stay current on state-of-the-art techniques and quickly evaluate what is worth building versus what is noise
• Lead cross-functional execution with stakeholders across product, engineering, and clinical teams
• Contribute to a team culture that is inclusive, intellectually honest, and moves with urgency