Author here. The data is mostly drawn from how people who work at these companies do in mock interviews rather than how our users do in real interviews with these companies.
> At interviewing.io, we’ve hosted over 100K technical interviews, split between mock interviews and real ones.
Something like "We analyzed 100K technical interviews to see which companies employ the people that we feel best performed in our mock interviews" would be more authentic
One of the things I learned from my years in research/academia is that Design Of Experiments in itself is a pretty complicated task. Most experiments/studies are invalidated due to a huge amount of confounding factors and correlations that are not factored in for the experiments.
A cursory visit to r/science comments would show a lot of people who do science for a living providing valid criticism to published peer reviewed scientific studies due to wrong Design of Experiments procedures.
Having lived all this first hand makes me EXTREMELY resistant to take seriously the data, analysis and conclusions of the linked article.
Other than that, the effort is appreciated and I like the ideas behind interviewing.io.