San Htut

Statistical Analyst & Researcher | 2x3 Factorial Experimental Design Project

• Designed a 2x3 randomized block factorial experiment in R, controlling geographic variance via nuisance blocking.
• Conducted power analyses and stratified randomization in R to determine optimal sample size and mitigate confounding bias.
• Modeled two-way ANOVA and interaction effects, visualizing key multivariate findings with ggplot2 for stakeholders.

Data Analyst / Researcher | Characterizing Law Enforcement Response to Vehicle Theft in Los Angeles

• Built an R data pipeline to clean, de-identify, and query 1M+ LAPD records, isolating 115,000+ vehicle theft cases.
• Trained multivariate logistic regression models, identifying statistically significant (p < 0.05) temporal and spatial risk factors.
• Ran longitudinal time-series decompositions to detect neighborhood crime surges and guide targeted resource allocation.

Data Science Consultant & Researcher | Statistical Modeling & Survival Analysis of Large-Scale UCLA Administrative Data

• Integrated 100K+ relational enrollment records to evaluate long-term instructional demand and post-COVID shifts.
• Deployed predictive models (Logistic Regression AUC = 0.7494, Random Forests) to forecast course under-enrollment risks.
• Modeled student attrition with Kaplan-Meier survival curves, delivering actionable curriculum consolidation strategies.