Clinician Scientist

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