Clinical Data Scientist, Real World Evidence
Tasks
- Apply machine learning to real world data
- Build reproducible data pipelines
- Communicate results to stakeholders
- Conduct comparative effectiveness analysis
- Create data visualizations and dashboards
- Develop phenotyping methods
- Develop predictive modeling
- Implement data quality checks
- Lead data integration
- Maintain version controlled pipelines
- Mentor analysts
- Perform causal inference
- Perform code review
- Perform natural language processing
- Prepare reports publications and presentations
- Present complex analyses clearly
- Resolve data and infrastructure issues
- Run survival analysis
- Support data governance
- Translate clinical questions into analytic plans
- Validate and monitor analyses and models
Perks/Benefits
- N/A
Skills/Tech-stack
Causal Inference | Claims data | Comparative Effectiveness | Comparative Effectiveness Research | Dashboards | Data Governance | Data Quality | Data Visualization | Data integration | Electronic Health Records | Health Records | Language Processing | Machine Learning | Natural Language | Natural Language Processing | Phenotyping | Predictive Modeling | Python | R | Registries | Reproducible Research | SQL | Survival analysis | Version control
Education
Roles
Regions
Countries
States
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