I am a versatile statistician and policy analyst whose work bridges public health, urban policy, and economic development. I apply methods such as Difference-in-Differences, Propensity Score Matching, Interrupted Time Series modeling, and Geographically Weighted Regression to examine spatially varying relationships across diverse populations. With experience integrating spatial and temporal data at multiple scales, I aim to produce research that informs evidence-based, locally tailored interventions directed at improving health equity, and population well-being. Proficient in R and Python, experienced with GIS tools, statistical modeling, spatial econometrics, and causal inference across local, national, and global contexts.