SME Information Technology Project Manager - Public Health Informatics
New
United StatesFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 10+ years
- Required Skills
- PythonSQLMicrosoft ExcelR
Requirements
- 10+ years of experience as a public health terminologist or in a related health informatics/IT role
- Deep expertise in public health coding and interoperability standards, including LOINC, SNOMED, ICD-10, USCDI+, HL7, and FHIR
- Strong understanding of vocabulary authoring methodologies and terminology management practices
- Proven ability to support data standards strategy and modernization initiatives within large-scale public health environments
- Experience mapping complex scientific, clinical, and laboratory data to standardized vocabularies
- Strong analytical and research skills with the ability to interpret complex surveillance and laboratory datasets
- Proficiency or familiarity with data tools such as Excel, SQL, SAS, R, or Python is highly desirable
- Bachelor’s degree required
- Master’s degree in Public Health, Epidemiology, Biostatistics, or Health Informatics preferred
- Strong communication, collaboration, and stakeholder engagement skills in multidisciplinary environments
Responsibilities
- Lead and coordinate initiatives focused on modernizing terminology systems and ensuring interoperability across clinical, laboratory, and epidemiological data environments
- Design and implement terminology and interoperability solutions integrating public health coding systems such as LOINC, SNOMED, ICD-10, and FHIR
- Provide strategic guidance on data standards, vocabulary authoring processes, and terminology tooling modernization to support federal public health initiatives
- Research and map complex laboratory assays and scientific data structures to standardized vocabularies for accurate surveillance and reporting
- Collaborate with internal and external development organizations to evolve existing standards and contribute to the creation of new public health informatics frameworks
- Analyze, validate, and enhance data quality using advanced data science approaches to support effective surveillance and reporting
- Ensure alignment of solutions with evolving interoperability standards and public health data modernization goals
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