Clinical Terminologist

Passionate about precision medicine and advancing the healthcare industry?

Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Our proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.

We now have more healthcare data than ever before, but providers often do not have the systems or expertise to make sense of all of this valuable data. We are building an infrastructure to modernize and enhance cancer treatment. We are on a mission to connect an entire ecosystem to redefine how data is used to improve patient outcomes. The RWD Clinical Informatics and Terminology team is seeking a highly-motivated and detail oriented Lead Clinical Terminologist who enjoys working with large and complex datasets to operationalize and QC the adoption of standard clinical terminologies into our data pipelines.

Responsibilities

• Collaborate with cross-functional teams to manage and update terminology services made available across the company.
• Maintain and extend modeled ontology solutions used throughout the company.
• Standardize clinical concepts from a variety of sources, including curated data, EHR integrations, and lab systems.
• Manage the adjudication of, and quality control pipelines for, new clinical concepts and domains.
• Proactively monitor and support quality assurance and process improvement initiatives.
• Monitor performance of production processes and recommend areas for improvement.

Qualifications

• 3+ years working with standard medical terminologies (e.g., ICD-CM-9/10, SNOMED CT, RxNorm, LOINC, CPT).
• Working knowledge of UMLS and familiarity with NCIm.
• Experience developing and maintaining clinical ontologic models.
• Experience working with real world data from various sources (e.g., EHRs, lab systems, claims, and abstraction or curation).
• Experience working with ELT tools to maintain high volume, high velocity data through-put pipelines.
• Familiarity with SQL, Python, and Semantic Web Technologies (RDF, OWL, SPARQL).
• Awareness of healthcare information standards, such as HL7 and FHIR for data exchange and interoperability.

Nice-to-haves

• Clinical background (PA, NP, RN, etc.).
• Experience with real world data analysis in Python or SQL.
• Participation in professional organizations (e.g., OHDSI, AMIA).
• Awareness of OMOP Common Data Model.