Senior Clinical Data Scientist
New
K
KariusClinical Metagenomics
Redwood City, CA (Hybrid) or Remote (USA)Full-TimeSenior
Salary133,824 - 200,736 USD per year
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Job Details
- Experience
- 5-6+ years (Bachelor's), 3-4+ years (Master's/MPH), or 1-2+ years (Ph.D.)
- Required Skills
- PythonSQLR
Requirements
- Bachelor’s degree in Health Informatics, Biomedical Informatics, Data Science, Computer Science, Biostatistics, Epidemiology, Public Health, or a related field with 5-6+ years of relevant experience.
- Alternatively, 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 or similar 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.
- Proficiency in Python and/or R for data transformation, cleaning, and quality assessment at scale.
- Familiarity with real-world data standards (OMOP CDM, CDISC, HL7 FHIR, SNOMED CT, ICD-10, LOINC).
- Experience supporting biostatistics or data science teams with dataset preparation and delivery.
- Strong technical communication skills for non-technical stakeholders.
- Knowledge of clinical trial data management principles and ICH-GCP is a plus.
Responsibilities
- Own EHR data extraction specifications for the AXIS registry, including data element definitions, data dictionaries, field mappings, and site-specific translation logic.
- Serve as the primary technical liaison to site informatics and IT teams to translate research data requirements into executable queries and protocols.
- Design and validate data extraction pipelines that ingest structured EHR data from multiple health systems into a harmonized format.
- Perform data quality assessment, anomaly detection, and cross-site consistency validation to resolve data integrity issues.
- Partner with the biostatistics team to deliver clean, documented datasets and support variable derivation for statistical analysis plans.
- Collaborate with clinical operations on site onboarding, data governance agreements, and technical feasibility assessments.
- Maintain registry data models, lineage documentation, and codebooks to ensure audit-readiness.
- Support broader clinical research analytics through dataset integration, file preparation, and visualization.
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