Data Scientist

RVO Health•Denver, CO

8h•Hybrid

About The Position

RVO Health is building an industry-leading healthcare platform that integrates the consumer health journey — helping people access the right information, care, and services at the right time. Formed through a partnership between Red Ventures and UnitedHealth Group, we combine world-class consumer analytics with one of the largest healthcare networks in the world. 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.

Requirements

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

Nice To Haves

Strong Python skills; experience deploying models in production environments
Familiarity with deep learning frameworks (PyTorch, TensorFlow) and NLP techniques (Transformers, LSTMs)
Experience with vector databases, embeddings, or retrieval-augmented generation
Hands-on experience with healthcare data (claims, EHR, or clinical text) is a strong plus
Demonstrated ability to move from research to production — not just notebooks
Comfortable working with cross-functional teams and communicating technical tradeoffs to non-technical stakeholders
Bachelor's or Master's in a quantitative field; equivalent industry experience considered

Responsibilities

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