The problem with AI and Data Science is that it relies on quantitative analysis, meaning metrics that are easily available and can be measured numerically. But when evaluating people, it's qualitative attributes that matter most. Rather than relying an algorithm to whittle down a list of 1,000 candidates, you may have better luck simply filtering on keywords like "SQL Server", manually reviewing the 100 most recently submitted resumes, and then lining up in person interviews with the 10 candidates that look the most promising. The DBA team themselves can set aside some time to review resumes. They know what to look for and have a vested interest in getting someone who's a good fit.