Projects (Work and Personal)

Current Experience: The Washington Post

Voterflow Inference

I developed a stratified regression model to estimate the share of a candidate’s votes in a prior election that is going to a new candidate in a current election.
pandas cvxpy PyMC Plotly matplotlib

Polling Averages

I co-developed our Bayesian Presidential polling averages, which generated over 9 million pageviews and was the most-read Politics story in 2024.
pandas NumPyro scikit-learn AWS Batch MySQL SQLAlchemy

Live Election Model

I contributed to our model that predicts who will likely win elections as votes are tabulated live. You can find the code for our Live Model on Github.
pandas cvxpy NumPy SciPy

Personalization

I also contribute to our site’s Personalization efforts and am currently conducting an extensive literature review and exploratory data analysis to identify the best-possible metrics we can use to measure product success.
pandas AWS Redshift scikit-learn matplotlib seaborn statsmodels

See all of my experience here

Side Projects

2025 New Jersey Governor's Race

I’m working on Bayesian polling averages to infer who will likely become the next Governor of New Jersey.
pandas PyMC matplotlib seaborn

Troon Brewing Release Prediction

Troon is a famous brewery in New Jersey that tends to release new beers whenever they are ready, without any advance notice. With this project, I’m trying to predict when the next Troon release will be. (tl;dr: It’s hard, but I’ve learned a lot about Bayesian modeling and uncertainty in the process.)
pandas PyMC matplotlib seaborn spaCy scikit-learn Prophet

Understanding Survey Weighting

I’m trying to gain a better understanding of survey weighting techniques, including raking and multilevel regression with poststratification.
pandas PyMC Bambi Samplics