Data Scientist

WellSky•Overland Park, KS

3d•Onsite

About The Position

The Data Scientist role focuses on turning clinical conversations into accurate, useful documentation, with deep emphasis on building and evaluating the model and agent workflows (the "harness") that make these solutions reliable. The role blends applied data science, large language model (LLM) evaluation, prompt and workflow engineering, and hands-on collaboration with product and clinical stakeholders to move ideas from prototype to trustworthy, production-ready capability.

Requirements

Bachelor's degree in a related field or equivalent work experience
2 - 4 years related work experience

Nice To Haves

Healthcare industry experience, especially with healthcare data.
Experience applying large language models or foundational models to speech, conversation, or documentation tasks.
Experience with cloud technologies, including modern API orchestrators
Experience designing evaluation methodologies for AI/ML or LLM systems (accuracy metrics, human review, annotation, error analysis).
Experience with ambient documentation, speech-to-text, or clinical documentation workflows.
Familiarity with infusion, home health, or ambulatory clinical workflows.
Experience building agentic workflows, prompt engineering, or tool-orchestrated LLM applications.
Proficiency in Python, and experience prototyping and iterating quickly alongside a product team.

Responsibilities

Partner with the product team in an exploratory, iterative fashion to design and prototype an ambient listening and documentation solution for the Home Infusion and Ambulatory Infusion space.
Apply foundational and large language models to transform clinical audio and conversation into accurate, structured, and clinically useful documentation.
Design, build, and refine the agentic harness (prompts, workflows, tool orchestration, and guardrails) that drives reliable ambient documentation.
Develop rigorous evaluation frameworks to measure documentation accuracy, completeness, and clinical soundness, including gold-standard datasets, human review, error-mode analysis, and ongoing quality monitoring.
Rapidly prototype and test approaches, using evaluation results to guide iteration and inform product direction.
Collaborate with product, engineering, and clinical stakeholders to translate exploratory findings into production-ready capabilities.
Contribute to responsible AI practices, including appropriate handling of sensitive healthcare data and attention to safety in clinical documentation.
Perform other job duties as assigned.