Clinician Scientist
Combines clinical expertise (MD/PA/DO) with AI to develop and refine tools for clinical documentation, decision support, and risk adjustment. Defines quality standards, optimizes prompts, evaluates outputs, and collaborates with engineering teams to enhance clinician efficiency.
About the job
What You’ll Do
- Develop and refine AI-driven clinical tools across notes, risk adjustment (HCC capture), clinical decision support, and prior authorization using clinical expertise and prompt engineering
- Define what “clinically meaningful” output looks like for each product area, including acceptable error rates, failure modes, and quality thresholds
- Collaborate with cross-functional teams (engineers, data scientists, clinicians) to integrate medical insights into AI models
- Write, review, and optimize prompts to improve AI model performance in clinical contexts
- Build and refine evaluation tools to streamline medical documentation quality assessment, including hallucination detection, omission detection, and medication safety checks
- Translate clinical needs into technical specifications and data models
- Define clinical guardrail metrics and baselines; own pre/post evaluation requirements for any model update that affects clinical output
- Contribute to product development, revenue cycle management, and broader business initiatives
- Monitor clinical guideline update cycles and flag when product behavior needs to evolve based on new standards or payer policies
What You’ll Bring
- MD, PA, DO (or equivalent clinical degree) with direct experience working in clinical practice
- Deep understanding of medical documentation, clinical workflows, and medical terminology
- Ability to evaluate AI-generated clinical notes, provide structured feedback, and guide improvements
- Strong knowledge of healthcare data standards (e.g., FHIR, HL7) and privacy regulations (e.g., HIPAA)
- Hands-on experience in clinical data validation and quality assessment
- Experience collaborating with engineers and product teams to build AI-powered clinical tools
- Strong analytical and problem-solving skills
- Excellent written and verbal communication skills
Nice to Have
- Experience in software engineering, particularly in prompt engineering or AI model development
- Python programming skills and experience with deep learning frameworks such as PyTorch, JAX, and/or TensorFlow
- Previous experience in AI-powered clinical documentation tools or clinical decision support systems
- Published research in AI, machine learning, or healthcare technology
Skills
Prompt Engineering, FHIR, Hl7, HIPAA, Python, PyTorch, JAX, TensorFlow, Ai Models, Clinical Data Validation
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