Encoding/Decoding Complexity

I integrate rigorous data science with policy-grade strategy and narrative clarity - then ship real, measurable change. Forged at the intersection of macro-systems thinking and quantitative biostatistics, my work bridges the gap between global socio-economic frameworks and actionable decision intelligence. My professional trajectory spans leading frontline epidemiological response teams during the COVID-19 pandemic, scaling enterprise analytics as a senior data scientist for a Fortune 24 organization, and driving agile, cross-functional teams across a Big 4 firm and an SF-based health startup. I don’t just build models; I translate complex statistical outputs into the strategic foresight required for senior leadership and public policy.

Given PhD-level training in Epidemiology, Biostatistics, and Neurocognitive Science, I am deeply technical but relentlessly applied. I am at home working in R, with extensive experience across Python, SQL/Postgres, Julia, SAS, and SPSS - however I often leverage Rust, C++, and Java as well. My technical wheelhouse includes wrangling mixed data, hypothesis testing, and architecting explainable machine learning pipelines - spanning supervised learning, clustering, and natural language. Beyond the algorithms, I build automated workflows, interactive geospatial maps, and cross-platform tools that live in the real world, such as my civic-insights platform, Perception Interval. My graduate training and research in neurocognitive science equips me with perspective and deep curiosity regarding human and artificial cognitive abilities - which I bring to the table in every machine learning and generative AI system that I design, build, deploy, and maintain.

Whether I am brainstorming with colleagues, communicating to expert & broad audiences, engineering insight systems, developing intelligence in a drop of cloud compute, or stepping into leadership roles in times of great challenge, my focus remains constant: extracting the signal from the noise, anticipating the range of probable futures, and building systems that drive human-centric, scalable impact.