Programming Languages

• Proficiency: Advanced

• Experience:

  • Conducted advanced statistical analyses, including regression modeling, hypothesis testing, and survival analysis, using R to derive actionable insights from complex datasets in healthcare and supply chain domains.

  • Leveraged R for data cleaning, visualization, and exploratory data analysis, creating interactive reports and dashboards that supported clinical research projects and quality improvement initiatives.

  • Applied R to analyze data from large platforms like N3C, performing multivariable regression, effect size calculations, and other advanced analytics to contribute to publications, posters, and presentations.

• Packages: dplyr, tidyr, skimr, survival, survminer, ggplot2. multcomp, stats, pwr, seminr.

Sample Code

• Proficiency: Advanced

• Experience:

  • Used Python for data analysis, statistical modeling, and automation, streamlining workflows in clinical research and supply chain optimization.

  • Developed and implemented machine learning models (e.g., Random Forest, Logistic Regression, SVM, Decision Tree, XGBOOST) and data augmentation (e.g., GAN, CTGAN, SMOTE) to predict outcomes and identify key trends and feature selection.

  • Performed exploratory data analysis, and created insightful visualizations to communicate complex findings effectively to stakeholders.

• Libraries: Pandas, NumPy, Matplotlib, Seaborn, Plotly, GeoPandas, Scikit-learn, Contextily, XGBoost, CTGAN, Imbalanced-learn.

Sample Code

• Proficiency: Advanced

• Experience:

  • Designed and optimized complex queries for data cleaning, transformation, data validation and aggregation, ensuring data integrity in clinical research and operational workflows.

  • Integrated SQL with Python and Tableau to extract insights from large relational databases, streamlining data analysis and visualization for impactful decision-making.

Sample Code