There's a huge variance between different schools, and an average grade from one university may be better than good grade from some different one. Additionally,

There's a huge variance between different schools, and an average grade from one university may be better than good grade from some different one. Additionally, I don't really ask questions that require some particular knowledge from algorithm classes -- it would be silly to determine whether someone is a good hire based on whether they remember details of, say, Hopcroft-Karp algorithm. On the other hand, many algorithm classes are all about this kind of stuff. So, I generally feel like it makes more sense to try to determine the actual aptitude when you have an opportunity, instead of trying to measure it by possible decades old proxy with huge and unknown variance. If you had good grade and/or spent some time studying for the interview, and really meet the hiring bar, you'll most likely do well in the interviews anyway. There's some noise in the process, and good qualified candidates are sometimes rejected, but from company's perspective, it's better to have some false negatives, than to give another metric that can be easily gamed, and get false positives. Google has enough qualified candidates applying for a job to make it not that big of a deal if you lose some due to the noise.