Blogs
Stats
- Andrew Gelman — daily posts on Bayesian modeling, causal inference, and how research goes wrong
- Richard McElreath — Bayesian modeling and cultural evolution, from the author of Statistical Rethinking
- Cosma Shalizi — dense, funny notebooks and book reviews on statistics and machine learning
- Rob Hyndman — forecasting, time series, and the craft of academic statistics
Data Science
- InstaCart — engineering and machine learning behind grocery delivery
- Netflix — experimentation, recommendation, and infrastructure at scale
- Airbnb — data science and engineering from the marketplace side
- Amazon Science — research across machine learning, economics, and operations
- Spotify Research — recommendation, experimentation, and causal inference
- Uber Engineering — marketplace experimentation and large-scale data systems
- DoorDash Engineering — logistics, forecasting, and experimentation
Economics, Marketing, Consulting
- Joel Cadwell (inactive) — R-driven marketing research and choice modeling
- Chris Chapman’s QuantUX — quantitative UX research, surveys, and conjoint
- John Cook — short posts on applied math, probability, and numerical computing
- Marc and Jeff Dotson — Bayesian marketing analytics in R
- Andrew Heiss — long, generous tutorials on causal inference and Bayesian methods in R
- Stephan Seiler’s Annual Best-of — yearly roundup of quantitative marketing papers worth reading
- Paul Goldsmith-Pinkham’s A Causal Affair — causal inference, coding, and consumer finance
- Kevin Bryan’s A Fine Theorem — long-form reviews of new economics papers
- John Cochrane’s The Grumpy Economist — macro, finance, and policy, plus writing advice for PhD students