Raul Landa
Principal Data Scientist
Raul Landa is a recovering ex-academic who uses internet measurements, analysis and modelling to design and build software to make our cache fleet more intelligent, adaptable, and self-tuning. Before Fastly, he built automated forecasting and capacity planning software, used wavelets to decompose fractal patterns in video traffic, and abused game theory and microeconomics to try and design incentive-compatible peer-to-peer networks. He is still into math, but he no longer uses Java or Matlab. Progress.
