Veronica Upadhyay
Profile
Hi I’m Veronica! I’m an M.S in Data Science student at UVA, with a Genomics focus. I hold a B.S in Statistics from UNC, with 2+ years of experience in predictive modeling and analytics for public health studies. I joined Well Dot, Inc. as an Data Analyst in Fall of 2025. In 2024, I was awarded the UNC SURF— a research grant to supporting my efforts of analyzing the probabilistic the risks of enteric illnesses among a youth population in Mozambique.
Contents
Education
M.S. Data Science • University of Virginia
REGARDS Scholar: NIH funded merit scholarship to do applied statistics research in genomics with UVA School of Medicine
B.S. Statistics & Analytics • University of North Carolina at Chapel Hill
SURF Awardee: Competitive stipend to conduct infection- risk- modeling research for a UNC School of Public Health study
Work Experience
Data Analyst, Workforce • Well Dot, Inc.
August 2025 to Present
- Independently built Python program that iterates local LLMs through chat data to programmatically assess engagement KPIs
- Edge computed with NLP models (spaCy + NLTK), automating 3+ hour logistics reporting task; now done in 10 minutes
- Programmed automation for utilization calculation; reduced data entry workload by 1 hour daily + eliminated entry errors
- Saving Operations department 8 hours per month with my automation that uses Google API to publish overtime requests
Operations Intern • Well Dot, Inc.
June 2025 to August 2025
- Used advanced SQL features like window functions and CTEs to pull data from BigQuery for ad-hoc reporting
- Refined algorithms that categorize consumer response types, identifying disengagement patterns for operational reporting
Undergrad Research Fellowship • Gillings School of Global Public Health (Brown Lab)
May 2024 to May 2025
- Awarded $4,000 for independent research on infection risks in a public health study funded by the Gates Foundation
- Modeled pathogenic infection risks by designing 6 Quantitative Microbial Risk Assessment models
- R programming to run beta- Poisson and Exponential models and quantify infection risks across varying ages
Statistical Programmer • Lineberger Comprehensive Cancer Center (Emanuele Lab)
Jun 2023 to May 2025
- Developed R program to automate correlation matrix calculations for 17,000 genes across 2,000 single cell RNA-seq datasets
- Used high performance computing to generate cell line dependency scores across 16 experimental conditions
Program Assistant • UNC Department of Applied Physical Sciences
Feb 2024 to April 2025
- Designed custom parts using Tinkercad and Adobe Illustrator to support engineering and biomedical research projects
- Supported users with 3D printing, laser cutting, and metalworks design
Data Analysis Researcher • Gillings School of Global Public Health
Aug 2022 to May 2024
- Automated most probable number computation with independent program, reducing lab data entry time by 10+ hours
- Processed and merged 3,000+ biological data points using dplyr, tidyr, and ggplot2 for pathogen prevalence analysis
- Assisted in analyzing enteric pathogen presence across 13 biological and environmental matrices
Projects
Disease Contraction Simulation (Python) Link
COVID-19 spread & recovery dynamic graphical visual
NBA Playoffs Models (R) Link
Build Machine Learning Models (Random Forest, Ridge Regression) to predict NBA scores
Digital Learning Habits (R) Link
Analyzed student engagement data for online learning platform; Duke DataFest 2024
Global Lemur Conservation (R) Link
Predicted life spans and reproduction habits using regression modeling
Choose Your Own Adventure (Python) Link
Game with functions for player input, random- movement, and game state tracking.
Conference Posters
“Quantitative Microbial Risk Assessment of Enteric Infections in Maputo, Mozambique” Upadhyay, V; Rao, G; Brown, J Celebration of Undergraduate Research, Chapel Hill, NC (Apr 2025)
“Microbial Characterization of Environmental Matrices in Maputo, Mozambique” Rao, G.; Holcomb, D.; Capone, D.; Lai, A.; Linden, Y.; Kowalsky, E.; Upadhyay, V.; Mataveia, E.; Cumbane, V.; Monteiro, V.; Chiluvane, M.; Brown, J.; Viegas, E. UNC Water and Health Conference, Chapel Hill, NC (Oct 2023)