Karius offers a competitive annual compensation range of USD 133,824 to 200,736, with remote-friendly work options from Redwood City, CA. In the Senior Clinical Data Scientist role, you will serve as the primary data architect for the AXIS real-world evidence registry, designing and operationalizing EHR data extraction pipelines across health systems and turning heterogeneous real-world data into analysis-ready datasets for biostatistics and clinical development. The position involves negotiating data specifications with site Epic Clarity teams and collaborating with biostatisticians to structure complex longitudinal datasets.
Responsibilities
- Lead the EHR data extraction specifications for the AXIS registry, defining data elements, data dictionaries, field mappings, and site-specific translation logic across diverse EHR environments.
- Serve as the main technical liaison to site informatics and IT teams, translating clinical research data needs into executable data queries and extraction protocols; hands-on experience with Epic Clarity and Caboodle is required.
- Design and validate data extraction pipelines that ingest structured EHR data (diagnoses, medications, labs, procedures, utilization) from multiple health systems into a harmonized, analysis-ready format.
- Conduct data quality assessments, anomaly detection, and cross-site consistency validation; implement processes to identify and resolve data integrity issues with sites.
- Partner with the biostatistics team to deliver clean, structured, and well-documented datasets; support data preparation, variable derivation, and dataset specifications for statistical analysis plans.
- Collaborate with clinical operations on site onboarding for clinical data integration, including support for data governance agreements, BAAs, and technical feasibility assessments.
- Build and maintain the registry data model, data lineage documentation, and codebook to ensure reproducibility and audit-readiness.
- Apply knowledge of real-world data standards (OMOP CDM, HL7 FHIR, SNOMED CT, ICD-10, LOINC) to support data harmonization across sites with diverse EHR configurations.
- Support seamless integration between EHR data, the registry EDC, and Karius' standardized internal clinical database.
- Support broader clinical research data analytics across programs, including integrating datasets from multiple sources, building analysis-ready analytic files, and data visualization to support clinical development and biostatistics teams.
- Contribute to the design of data collection strategies for future real-world evidence studies and registry expansions.
Requirements
- Bachelor’s degree in Health Informatics, Biomedical Informatics, Data Science, Computer Science, Biostatistics, Epidemiology, Public Health, or a related quantitative or clinical field with 5-6+ years of relevant experience; a master’s degree or MPH with 3-4+ years of relevant experience; or a Ph.D. with 1-2+ years of relevant experience.
- Minimum 4+ years of hands-on experience with Epic Clarity and/or other systems; ability to write and optimize SQL queries against large clinical data warehouses.
- Demonstrated experience designing or executing EHR data extractions for research or registry studies, including direct engagement with health system informatics or IT teams.
- Proficiency in Python and/or R for data transformation, cleaning, and quality assessment at scale.
- Familiarity with real-world data standards including OMOP CDM, CDISC, HL7 FHIR, SNOMED CT, ICD-10, and LOINC.
- Experience supporting biostatistics or data science teams with dataset preparation, variable derivation, and analysis-ready data delivery.
- Ability to communicate technical data concepts clearly to non-technical clinical site staff, research coordinators, and clinical operations colleagues.
- Experience with large, multi-site, longitudinal real-world datasets is strongly preferred.
- Knowledge of clinical trial data management principles and ICH-GCP is a plus.
Technologies
Technologies: Epic Clarity, Caboodle, SQL, Python, R, OMOP CDM, HL7 FHIR, SNOMED CT, ICD-10, LOINC
Reports to: Director, Clinical Statistics and Data Management
Location: Redwood City, CA or Remote
