Data Science · Biostatistics · R & Python
Data scientist & biostatistician
My work spans clinical trials, real-world evidence, claims, observational studies, and biomedical data. I lead analysis projects end to end: defining the question, carrying out the statistical work, building supporting software, and communicating the results.
What I do
Healthcare data analysis
Most of my work involves leading analysis projects end to end: deciding what questions to ask, choosing an appropriate approach, carrying out the analysis, and building tools that help teams understand the results.
01
Healthcare data
Clinical trials, real-world evidence, claims, observational cohorts, patient-reported outcomes, and biomarker data.
02
Statistics and machine learning
Survival and longitudinal analyses, causal inference, mixed-effects models, simulation, predictive modeling, and subgroup analyses.
03
Analytical software
Reproducible workflows, R packages, Shiny applications, dashboards, testing, and deployment using R, Python, and related tools.
Selected projects
Public software
R package · v0.2.0
shinydataviewer
A reusable Shiny module for viewing tabular data with a searchable table and variable-summary sidebar.
Shiny application · Public dashboard
Massachusetts Water Quality
An interactive dashboard for exploring Massachusetts water-quality data by municipality and chemical. An update using newer or streaming data is planned.
Background
Experience across healthcare data
My experience spans biopharma, contract research, and real-world data. Across these settings, I have worked cross-functionally with clinical, translational, medical affairs, biostatistics, data science, data engineering, IT, and operational teams.
In senior roles, I have led technical work, helped set standards for code quality and validation, and mentored colleagues. I care about clear communication, reproducible analysis, and tools that other people can maintain.