Data Scientist

RVO Health•Minneapolis, MN

10h•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, RVO Health combines world-class consumer analytics with one of the largest healthcare networks globally. The team is composed of data scientists, machine learning engineers, analytics engineers, data engineers, and product managers, valuing diverse and inclusive teams. The company is seeking a Data Scientist to join a fast-moving team focused on building ML and AI solutions for consumer health behavior change products. In this role, the Data Scientist will work on problems where their models directly influence real health outcomes for millions of users, operating in an environment that moves fast, iterates often, and thrives in ambiguity.

Requirements

Comfortable owning problems end-to-end, shipping fast, and adjusting course when the data or product direction changes
Experience building applications with LLMs, prompt engineering, RAG pipelines, LangChain, or similar tooling (Generative AI & LLMs)
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 (Evaluation & Measurement)
Extracting structured insights from unstructured clinical text and/or working with medical claims data to understand patient journeys, diagnoses, and treatment patterns (Clinical NLP & Claims Data)
Building systems that help users find relevant health information, including semantic search, dense retrieval, and RAG architectures (Search & Retrieval)
Understanding user engagement, retention, and habit formation patterns in the context of health behavior change (Behavioral modeling)

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