Clinical Informaticist

Identify, analyze, and resolve clinical data quality issues across Aledade's multi-vendor EHR ecosystem. Investigate root causes of data discrepancies at the interface, configuration, and source system level. Produce structured findings with actionable recommendations for engineering and integration teams.

Map clinical data elements to standardized code systems and validate mapping accuracy across clinical domains. Support the development and maintenance of Aledade's terminology mapping capabilities, including rule-based and AI-assisted approaches.

Support quality measure programs by ensuring clinical data completeness and accuracy throughout the reporting pipeline. Validate measure logic and code sets against published specifications. Identify data gaps impacting measure performance and collaborate cross-functionally to resolution..

Serve as the clinical subject matter expert for new data sources, AI-powered extraction, and interoperability initiatives. Provide clinical context to engineering, product, and operations teams for data governance, vendor engagement, and process improvement efforts.

Bachelor’s or Master’s degree in Nursing, Medical/Health Informatics, Bioinformatics, or a related field.

5+ years in clinical informatics, healthcare data analysis, or health information management

Strong skills in querying, analyzing, and validating clinical data (experience with Databricks/Spark SQL a plus)

Solid understanding and experience with standard Health Information Technology (HIT) vocabularies and terminologies.

Hands-on experience with one or more ambulatory Electronic Health Record (EHR) systems.

Deep knowledge of C-CDA/CCD document structure, HL7 standards, and how clinical data is represented in structured exchange formats

Experience with quality measure specifications (eCQM, MIPS, MCQM, HEDIS, etc) and understanding of how clinical data supports measure calculation

Demonstrated ability to investigate complex data issues, identify root causes, and communicate findings clearly to both technical and non-technical stakeholders

Experience with cloud-based data platforms (Databricks, AWS, Snowflake) for large-scale clinical data analysis and data management

Familiarity with FHIR resources and modern healthcare interoperability standards

Understanding of working with Health Information Exchanges (HIE) or TEFCA data flows

Knowledge of healthcare data governance and best practices in maintaining data integrity and security.

Understanding of population health management and the data infrastructure that supports it.

Certification in clinical informatics or health information management (e.g., CPHIMS, CAHIMS) is advantageous.

Experience in applying machine learning or AI technologies within healthcare settings.

Familiarity with healthcare data governance, provenance tracking, and regulatory requirements for clinical data use