Here's a sample of data projects I've built and/or directed.
Superstorm Sandy: Deadly topology
This was a challenge: How to clearly illustrate a story reporters at WNYC were working on about how a bowl-shaped neighborhood on Staten Island saw a high concentration of deaths in the storm — likely because they were caught off guard by water rushing into that basin. I worked from an open data set of elevation contours to design and build this map, experimenting with the data and presentation until I got it as clear as possible. The deployed version, which no longer functions, was a "slippy map" you could pan and zoom.
The cops behind NYPD "resisting arrest" arrests
While the illustration is simple, the work behind it was not at all. The WNYC data news team I led, working with an investigative reporter at the station, analyzed five years of court records to show that a small percentage of NYPD police officers were behind the majority of the "resisting arrest" charges, a charge known to be used to justify use of force.
"Resisting arrest" in black and white
In that same series, our team discovered that among those arrested for drug crimes, disorderly conduct, and theft, NYPD officers were fare more likely to add "resisting arrest" charges for black suspects than for white suspects. Since we looked at the pool of people already arrested, this calculation showed a bias beyond the systemic racial imbalance of overall arrests.
A bot to monitor federal courts
I built a bot that watched federal court filings for specific criteria and fed what it found to former Quartz reporter Justin Rohrlich. He used that information as the basis for nine scoops.
Mining the Luanda Leaks with machine learning
Our team at Quartz helped journalists from around the world use machine learning to mine 700,000 documents detailing how Isabel dos Santos siphoned hundreds of millions of dollars out of Angola, We used machine learning to help reporters locate tax documents, board minutes, and other key pages buried in the trove.