Clinical Informatics Data Scientist

Job description

A leading healthcare organization is seeking a Clinical Informatics Data Scientist to help make complex clinical datasets accessible, standardized, well-documented, and ready for analytics and AI use cases.

The position combines clinical informatics, healthcare analytics, data standards, and hands-on SQL work. The Clinical Informatics Data Scientist will develop reusable clinical data assets, establish documentation and quality standards, and help analysts, data scientists, and business stakeholders use clinical information appropriately.

Responsibilities

• Develop expertise in clinical data structures, including Continuity of Care Document (CCD) data, laboratory results, clinical notes, and administrative healthcare data.
• Build reusable clinical data assets, including tables, views, and analytical features that support reporting, analytics, and AI and machine learning use cases.
• Establish standards, documentation, and best practices for reusable clinical data features.
• Create and maintain data dictionaries, lineage documentation, business rules, known limitations, and appropriate-use guidance.
• Develop SQL queries, dashboards, and visualizations that communicate clinical data availability, quality, and analytical findings.
• Translate clinical concepts into analytical frameworks that can be understood by technical and nontechnical stakeholders.
• Partner with data engineers to inform ingestion, transformation, and storage approaches for clinical datasets.
• Validate and monitor clinical data for quality and usability.
• Support analysts, data scientists, and business users through documentation, training, and consultative guidance.
• Apply healthcare data governance, privacy, and security practices, including HIPAA requirements.
• Work with healthcare interoperability and terminology standards, including HL7, FHIR, ICD-10, SNOMED CT, LOINC, CPT, NDC, and RxNorm.

Required experience and skills

• At least 2 years of relevant experience in clinical informatics, healthcare analytics, or clinical data management.
• Familiarity with clinical datasets such as CCD data, laboratory results, clinical notes, and administrative healthcare information.
• Knowledge of healthcare coding and terminology systems, including ICD-10, CPT, HCPCS, SNOMED CT, LOINC, NDC, and RxNorm.
• Strong SQL skills and experience analyzing large healthcare datasets.
• Familiarity with cloud data platforms, preferably Google Cloud Platform and BigQuery.
• Understanding of healthcare data quality practices, including profiling, validation, and monitoring.
• Ability to support downstream data consumers through clear documentation, training, and consultation.
• Strong written and verbal communication skills with the ability to explain clinical data concepts to technical and business audiences.
• Experience with healthcare interoperability and harmonization standards such as OMOP, CCDA, and FHIR is preferred.
• Experience with clinical workflows and health information exchanges is preferred.
• Experience applying standardized terminology such as UMLS within common data models such as OMOP is preferred.
• Experience designing and implementing ETL processes that transform heterogeneous clinical sources into standardized models, preferably the OMOP Common Data Model, is preferred.
• Experience designing clinical data quality frameworks is preferred, including frameworks or tools such as Achilles and Data Quality Dashboard (DQDB).
• Knowledge of healthcare privacy and security practices, including HIPAA, HITRUST, de-identification, tokenization, PHI handling, and row- or column-level access controls, is preferred.
• Bachelor's degree in health informatics, public health, nursing, health information management, computer science, statistics, or a related quantitative or clinical discipline, or an equivalent combination of education and experience.
• Master's degree or higher in health informatics, biomedical informatics, clinical informatics, public health, epidemiology, or a related discipline is strongly preferred.
• A clinical background with a transition into informatics or analytics is highly valued.