Clinical AI Data Specialist

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $120k - $145k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Artificial Intelligence

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Datavant

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2017

⚕️ Healthcare Insurance

☁️ SaaS

🏢 Enterprise

💰 $40M Series B on 2020-10

Healthcare Insurance • SaaS • Enterprise

Datavant is a company that provides a platform and network focused on making health data secure, accessible, and usable across the healthcare ecosystem. With a focus on data connectivity and interoperability, Datavant facilitates the movement of healthcare records across a vast network of organizations, including hospitals, clinics, health systems, and data partners. Their suite of products and solutions covers areas such as health data exchange, data transformation, and privacy compliance, serving various clients including health plans, healthcare providers, life sciences, and government organizations. Datavant's mission is to advance human health through improved data exchange and analytics.

📋 Description

• Annotate medical records for AI training data • Validate annotated data to ensure quality • Refine the clinical logic behind AI outputs • Provide clinical coding & HIM subject-matter expertise to data science • Read and interpret clinical documentation — physician notes, assessment and plan sections, problem lists, medication records — to identify codeable diagnoses, conditions, and other clinical entities (document boundaries, type, author, section), applying ICD-10-CM and risk adjustment coding standards and mapping to clinical ontologies (ICD-10-CM/PCS, CPT, RxNorm) when required by project scope • Distinguish conditions that meet documentation standards for coding from those that do not, exercising clinical judgment independently, and flag ambiguous or edge-case documentation with written rationale • Review AI model output labels against clinical documentation to identify false positives, false negatives, and specificity errors; clean and correct label datasets and categorize error patterns for the data science team • Apply coding knowledge to evaluate whether model-generated code assignments are clinically and regulatorily supportable, and escalate systematic quality issues that may indicate model behavior problems • Translate ICD-10-CM and coding guideline requirements into explicit, testable instructions — LLM prompt language and computable coding rules — using AI-assisted tools testing revisions against curated ground-truth datasets and iterating on observed failures • Document the clinical rationale and precision/recall impact of each prompt or rule change for senior review

🎯 Requirements

• Domain expertise with a minimum 5 years of coding and/or CDI experience with demonstrated proficiency in ICD-10-CM code assignment from clinical documentation • Active credential in at least one of: CCS, CPC, CRC, CDIP, CCDS, or equivalent AHIMA/AAPC certification • Ability to apply clinical coding standards consistently and independently to produce high-quality, reproducible labels across large document sets, catching subtle distinctions that affect code assignment • Ability to articulate the clinical rationale behind a labeling decision in writing for QA and audit, and to express coding requirements as explicit, unambiguous instructions — the discipline behind a well-constructed coding query • Works independently within established guidelines without case-by-case direction on routine annotation, and escalates systematic issues — repeated error patterns, guideline gaps, documentation quality trends — rather than resolving them in isolation

🏖️ Benefits

• Comprehensive health, dental, and vision insurance • Paid time off (PTO) plan, offering X days per year, plus holidays • Retirement savings plan • Flexible work arrangements • Opportunities for career growth and development • Employee wellness programs