Clinical Data Scientist/ Methodologist
Tasks
- Apply NLP for clinical note extraction
- Apply propensity score methods
- Assess patient population representativeness
- Assess proxy endpoints and surrogate endpoints
- Collaborate with analysts and data scientists on implementations
- Conduct feasibility assessments for real world data sources
- Conduct sensitivity analyses and bias assessment
- Develop data assessment frameworks
- Document feasibility results in reports
- Ensure correct medical coding for patient identification
- Evaluate data quality dimensions
- Extract structured and unstructured clinical data
- Manage external data vendors and technology partners
- Partner with cross functional stakeholders on data identification and usage
- Perform time to event analyses
- Recommend fit for purpose real world data usage
Perks/Benefits
Skills/Tech-stack
Bias Assessment | Biostatistics | CPT | Claims data | Data Quality | Data extraction | Data quality assessment | Descriptive Statistics | EHR data | Epidemiology | Event analysis | ICD-10 | LOINC | Language Processing | Machine Learning | Natural Language | Natural Language Processing | OHDSI OMOP | OHDSI OMOP CDM | OMOP-CDM | Pharmacoepidemiology | Predictive Modeling | Propensity Score Matching | Propensity score | Python | Quality Assessment | R | Real-World Data | Real-World Evidence | Regression Analysis | RxNorm | SAS | SNOMED CT | SQL | Score Matching | Sensitivity Analysis | Snowflake | Time to Event | Time to event analysis
Education
Roles
Clinical Data Scientist | Data Scientist | Epidemiologist | Scientist
Regions
Countries
States
Cities
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