Hello! I'm Jacob. I'm a data scientist/economist. A lot of my work is focused on the design and analysis of experiments to improve decision making. For example, trying to understand the impact of formalizing land tenure rights in Tanzania through digitial land certificates or understanding what changes in subscription rates are the result of seasonality or product upgrades. In my day job these days, I use Bayesian models and descriptive statistics to gain a deeper understanding of customer interests and behavior in youth sports.
A brief list of stuff I like to work on:
- Food, music, and basketball
- Learning how to create accessible AI agents that enhance rather than replace colleague's work
- Causal inference
- Thoughtful descriptive analysis
- The Graph that Haunts Me: Presentation delivered to the DC Data Science Community Meet-up about how metrics, even ones we use and cite, can be simultaneously flawed and unavoidable.
- Bayes Dash: developed to help teach colleagues Stan and to explain prior distributions.
- How Fast Does New York Fix It?: after realizing my priors for the city's response time to 311 calls were way off, I decided to create a map and fit a hierarchical emprical Bayes model to 311 data by census tract to see how likely a call is to get addressed.
- Wizards Points: repo for my NBA Substack heavy on data viz