About the editor
Data scientist in Bozeman, Montana, writing about models, evidence, and the places where useful simplifications break.
I'm Daniel Flavin — a data scientist who can't stop writing about the things the data turns up. Wrong Models Only is my one-person paper: part portfolio, part open notebook, written for anyone who likes to know how the world actually works.
By day I work on retail pricing, demand forecasting, and the measurement systems that decide whether a model actually helped. The blog is where I slow that work down, separate the useful simplification from the convenient fiction, and explain the idea well enough that a curious stranger can audit the reasoning.
I write toward the job I want: somewhere between the analysis and the story, where rigor and curiosity aren't a trade-off.
How this paper works
I write in spirals. A topic starts with an approachable first pass — the big idea, no jargon, something you could read on a train. Then I circle back with deep dives that add the math, the code, and the caveats, and usually a project where I actually build the thing.
Each spiral is a thread you can trace from first curiosity to finished tool — so you can stop at whatever depth you came for, or follow me all the way down. I'm learning in public; the threads are the trail.
Forecasting Citi Bike demand
A decision layer for one-day Citi Bike demand: conformalized quantile forecasts that restore 80% interval coverage, a 90th-percentile newsvendor rule for rebalancing, and an ops memo that turns uncertainty into a truck plan.
Which forecast should you trust?
A granularity-and-horizon audit of ten demand-model families on 110M Citi Bike trips: the daily champion is the worst annual accountant, nothing honest beats "same day last year" at 90 days, and equal information makes a zero-shot foundation model tie a tuned tree. Final champion: the arithmetic mean.
Citi Bike weather station explorer
A MapLibre station explorer for 2023 Citi Bike demand: filter by temperature band, rain, time of day, and day type to see which parts of the network move with the weather.
The beats
The toolkit
Technologies represented in the published projects and this site.
Open to data-science roles where the work is rigorous and the explaining matters. The resume is available here, and the clearest public sample of the work is the project archive.