About
Hey, I’m Ryan, a Data Science Fellow at VoteHub. I’m 🇨🇦 Canadian and 🇺🇸 American.
At VoteHub, I sit on the data science team and the decision desk. I built a small but important piece of our midterm model, the first of its kind to carry precinct-level geospatial and ecological inference estimates for 175,000 precincts nationwide. More recently I built our Voter Power Index.
Closer to home, I was the volunteer finance lead on Daniel Biss’s campaign for Congress in Illinois’s 9th District, which meant that for a while I saw the fundraising numbers I usually read in FEC filings from the other side of the ledger.
From when I was 7 or 8, my dad brought home Bloomberg Businessweek every week or so, as the name suggests. I would lift it off the newel post and read it pretty religiously; I think reading it changed my life.
In my free time, I like to shoot photos, go on long runs, swim for my team, and write on Expected Values, my Substack, where I published the DeepSky Partisan Estimator, a model that estimates precinct partisanship from satellite imagery and census data. I think onion futures should be tradable! DeepSky, along with most of what I build on my own or with friends, now lives at Cohese, a small lab for computational political geography that we hope stays as fun as it has been so far. That includes Shoal, a sampler that draws neutral redistricting plans on a laptop GPU many times faster than the standard tools, and Tessera, a free Mac app for drawing district maps and watching them in 3D, with precinct data for every state. I was a prolific politics and AI trader on Manifold, too, and still sit roughly in the top 0.25% of 160,000 traders by profit, with a 2.6 realized Sharpe.
I write things up in 
because I think it looks cool and because Overleaf is better than Google Docs. Take a round trip in the wind, or read a motley crew of my quotes.
When I’m not doing any of the above, I’m a junior at Evanston Township High School.
nonexhaustive interests
- onion futures contracts
- satellite imagery, and how conducive it is to political geography and inference
- deep(ish) learning models
- elex and voting science
- multi-scale overlap averaging
- redistricting ensembles and chain sampling
- photography
- the efficiency of play-money prediction market sites
- the economics of inference and GPU time
- the future of how humans will interact with the world
- monetary policy, broadly
- Benford’s law
- the mech interp of Pangram’s AI detection models
Email: rymccomb1@icloud.com