Clinical Terminology Architect — Ontologies & Data

Tempus AI, Inc.; Chicago (IL); On-site; USD 67,000 - 95,000; Full time

Benefits offered by this job

Benefits package

Job summary

Tempus AI, Inc. in Chicago is seeking a Clinical Terminologist to operationalize and QC standard clinical terminologies within Tempus data pipelines.

You will work with large-scale real-world data and collaborate with cross-functional teams to standardize concepts from EHRs, labs, and claims. The role emphasizes developing and maintaining ontologic models, ensuring high-volume data throughput, and leveraging ELT tools alongside semantic web technologies (RDF/OWL/SPARQL).

Qualifications

• 3+ years working with standard medical terminologies (e.g., ICD-CM-9/10, SNOMED CT, RxNorm, LOINC, CPT).
• Familiarity with UMLS and NCIm.
• Experience developing and maintaining clinical ontologic models.
• Experience working with real world data from EHRs, lab systems, claims, and abstraction or curation.
• Experience working with ELT tools to maintain high volume, high velocity data through-put pipelines.
• Awareness of HL7 and FHIR for data exchange and interoperability.

Responsibilities

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

Skills

Terminology services

Ontology modeling

SNOMED CT

LOINC

CPT

ICD-CM-9/10

SQL

Python

HL7/FHIR awareness

Tools

ELT tools

RDF/OWL/SPARQL

UMLS

Job description

Tempus AI, Inc. in Chicago is seeking a Clinical Terminologist to operationalize and QC standard clinical terminologies within Tempus data pipelines.

You will work with large-scale real-world data and collaborate with cross-functional teams to standardize concepts from EHRs, labs, and claims. The role emphasizes developing and maintaining ontologic models, ensuring high-volume data throughput, and leveraging ELT tools alongside semantic web technologies (RDF/OWL/SPARQL).