Hi there! My name is Whitney Zhang.
I am a Data Analyst and Researcher focused on using data in a meaningful way.
I believe that behind every dataset is a human story waiting to be understood.
With a background in digital health innovation and a Master’s in Business Analytics from the University of Michigan, I specialize in turning complex data into clear, reliable, and impactful insights. My work is dedicated to ensuring that data is used responsibly and effectively to support better decision-making in research and community-based organizations.
Check out some of my recent projects:
Academic case study: Using unsupervised clustering and outlier detection models on breast cancer data to select high-precision patient candidates for clinical trial.
Clinical Trial Participant Identification
Academic case study: Using mixed integer programming to construct an optimization model for a beer company’s manufacturing and distribution network in Excel, then CPLEX.
Supply Chain Optimization Model
Areas of Expertise:
Statistical Analysis
Multivariate Regression
Survival Analysis
Causal Inference
Experimental Design/Power Analysis
Hypothesis Testing
Machine Learning
Tree-based Models
Ensemble Methods
Unsupervised Clustering Methods (DBSCAN, Hierarchical, K-means)
Supervised Classification Methods (SVM, Logistic Regression, K-Nearest Neighbors)
Artificial Neural Networks
Dimensionality Reduction (PCA)
Programming Languages/Tools
R (tidyverse, ggplot2, caret)
Python (Pandas, Seaborn, Scikit-learn)
SQL
CPLEX
Tableau
Power Query