I work on analytics, publication support, and technical projects with an emphasis on reliable workflows, readable outputs, and useful follow-through.
I am a New York-based data analyst with experience across research operations, clinical data work, publication support, and graduate study in data science. I like work that takes complicated information and turns it into something dependable, readable, and genuinely useful.
Research analytics
2+ years
Data analysis and study support at Mount Sinai
Graduate study
M.S. Data Science
Pace University, 3.96 GPA
Peer-reviewed work
8 publications
Direct co-authorship plus broader study-group publication support
Featured GitHub project · 2025-Present
Built a Twitch audience-mapping pipeline that collects audience-presence data, models shared-viewer overlap, and visualizes community structure.
Direct co-author paper · 2026
Direct co-author on a Vaccine paper examining durable humoral SARS-CoV-2 responses in solid organ transplant recipients with and without HIV.
Additional public project · 2026
A SwiftUI iOS day-planner built around daily checklists, a daily digest, reminders, and a home-screen widget.
The goal is not just clean analysis. It is making sure the output is understandable, reliable, and useful once it leaves the notebook.
I like taking messy source data and turning it into work that is reproducible, explainable, and easy for other people to use.
A strong analysis only goes so far if the figure, writeup, or handoff does not make sense to the next person in the room.
I am comfortable moving between analysis, documentation, dashboards, and project support when that is what helps the work move forward.