Role - Knowledge Engineer
Location - San Francisco, California/ Remote
Experience - 8+ Years
A minimum of three years’ experience in clinical informatics, clinical knowledge development or clinical knowledge testing
Experience with the application of clinical informatics, including definition and implementation of clinical data models; and creation and management of computable clinical rules
Experience with clinical decision support or quality measurement in electronic medical records or population health platforms
Experience programming in the Clinical Quality Language (CQL)
Experience programming in Python or Clojure
- Translate qualitative clinical guidelines, logic, and required data input into executable knowledge artifacts represented as CQL expressions against FHIR data.
- Build and execute unit test cases to validate knowledge artifacts
- Develop and test computable knowledge artifacts with large data sets
- Manage and track the progress of computable knowledge artifacts through a predefined development process.
- Respond to ad-hoc analysis requests while supporting core pipeline development.
- Develop new tools and solutions to support artifact development and testing processes
- Drive the team’s business results through data-based insights and the ability to engage with a wide range of stakeholders and functional teams.
- Identify inefficiencies, optimize processes and dataflows, and make recommendations for improvements.
Specific Skills and Knowledge
• Demonstrated performance in framing ambiguous business problems and driving toward a solution hypothesis, while working independently to resolve issues.
• Meticulous with strong analytical and critical thinking skills.
• Demonstrated experience in proactive communication across all levels of the business hierarchy
• Expertise in dealing with large datasets using analytical approaches and quantitative methods
- Demonstrated expertise in the CQL programming language for complex clinical analysis
Thanks and Regards