Note: The job is a remote job and is open to candidates in USA. Karius is a life science, venture-backed clinical metagenomics company, focused on elevating patient care through microbial insights. The Sr. Clinical Data Scientist will serve as the primary data architect for Karius’s large-scale commercial real-world evidence registry, responsible for designing and operationalizing EHR data extraction pipelines and transforming heterogeneous real-world data into analysis-ready datasets.
Responsibilities
- Own EHR data extraction specifications for the AXIS registry, including data element definitions, data dictionaries, field mappings, and site-specific translation logic across heterogeneous EHR environments
- Serve as the primary technical liaison to site informatics and IT teams, translating clinical research data requirements into executable data queries and extraction protocols; primary experience with Epic Clarity and/or Caboodle 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
- Perform data quality assessment, anomaly detection, and cross-site consistency validation; implement processes to identify and resolve data integrity issues with sites
- Partner closely with the biostatistics team to deliver clean, structured, well-documented datasets; support data preparation, variable derivation, and dataset specifications for statistical analysis plans
- Collaborate with clinical operations on site onboarding for clinical site 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 working knowledge of real-world data standards (OMOP CDM, HL7 FHIR, SNOMED, 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
Skills
- 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
- Strong technical aptitude, including the ability to write and interpret complex SQL queries
- Ability to translate technical clinical data requirements into clear, practical guidance for non-technical stakeholders
- Strong attention to detail and comfort working with complex data sharing specifications
- Intellectual curiosity and sound judgment when evaluating clinical data, workflows, and downstream implications
- Ability to move fluidly between hands-on technical work and stakeholder-facing communication
- Collaborative communication style, with the ability to partner effectively with site coordinators, clinical teams, and cross-functional stakeholders
- Experience with large, multi-site, longitudinal real-world datasets strongly preferred
- Knowledge of clinical trial data management principles and ICH-GCP a plus
Company Overview
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