Data Science Engineer · PharmD

Kevin Lan

Clinical Informatics & Real-World Data Specialist

PharmD by training, data engineer by trade. I came up through the CDC's Public Health Informatics Fellowship and spent the years since building OMOP CDM models and FHIR pipelines in Python, SQL, and R. My focus is real-world evidence and clinical interoperability, because claims and EHR data are only useful once someone's made them trustworthy.

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Currently

Data Science Engineer @ Cercle AI

Harmonizing multi-source claims and EHR data into OMOP CDM-style models, authoring statistical analysis plans, and serving as the client-facing data lead on real-world evidence work for pharma partners.

What I work with

Real-World Data

Administrative claims & EHR harmonization, OMOP CDM, cohort design, statistical analysis plans.

Interoperability

FHIR, HL7 v2/CDA R2 (certified), SNOMED CT, RxNorm, LOINC, USCDI/USCDI+.

Real World Data Analytics Engineering

Python, R, SQL, Airflow, Neo4j/Cypher, Azure (Data Factory, Databricks, Synapse).

Skillset

OMOP CDMSNOMED CTRxNormLOINCHL7 v2 / CDA R2FHIRUSCDI / USCDI+PHIN-VADRPythonSQLAirflowNeo4j / CypherAzure (Data Factory, Databricks, Synapse)R ShinyStatistical Analysis Plans

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