Skills
Skills
An inventory of tools, languages, and domains I work with. Proficiency levels reflect depth of regular use, not a self-assessment exam.
Programming Languages
- R – primary language, 15+ years
- SQL – Azure Data Warehouse, T-SQL, complex cohort queries
- Python – data engineering, tooling (txtarchive)
- SAS – legacy healthcare analytics
R Ecosystem
- tidyverse
- tidymodels
- ranger
- targets
- Quarto
- shiny
- gt / gtsummary
- survival / survminer
- kernelshap / shapviz
- pROC / yardstick
Machine Learning & Statistics
- Random Forests
- Logistic Regression
- Survival Analysis
- SHAP Interpretation
- Cross-Validation
- Calibration & Thresholding
- Clustering / Peer Groups
- Causal Inference (emerging)
Healthcare & Clinical Data
- EHR / Claims Data
- Cohort Development
- Sickle Cell Disease
- LOINC / ICD Coding
- Clinical Trial Design
- Real-World Evidence
- Risk Stratification
Infrastructure & Tools
- Azure Data Warehouse
- Git / GitHub
- Linux / Ubuntu
- Docker
- Netlify
- Claude Code / AI-assisted development
Proficiency levels: expert = daily use, deep knowledge | advanced = regular use, strong proficiency | working = functional, growing