Clinical Data Scientist
Tasks
- Apply ICD and procedure code based patient identification
- Apply epidemiological and biostatistical methods
- Assess bias and confounding
- Assess patient population representativeness
- Collaborate with analysts and data scientists
- Conduct propensity score methods
- Conduct sensitivity analyses
- Conduct time to event analyses
- Design fit for purpose RWD recommendations
- Develop data assessment frameworks
- Document standardized feasibility reports
- Evaluate data quality dimensions
- Evaluate structured and unstructured data extraction
- Identify RWD source limitations
- Lead RWD feasibility assessments
- Manage external data vendors and partners
- Perform NLP based clinical note extraction
- Provide surrogate endpoint applicability guidance
- Recommend optimal medical coding standards usage
- Serve as methodological point of contact
Perks/Benefits
Skills/Tech-stack
Administrative Claims | Bias Assessment | CPT | Data Quality | Data quality assessment | EHR | Event analysis | ICD-10 | LOINC | Medical coding | NLP | OHDSI OMOP | Predictive Modeling | Propensity Score Matching | Propensity score | Python | Quality Assessment | R | Regression Analysis | RxNorm | SAS | SNOMED CT | SQL | Score Matching | Sensitivity Analysis | Snowflake | Time to Event | Time to event analysis
Education
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