Description
PyData SF 2016
Matching candidates with openings: defining features across several sets of Data Scientist selection criteria, using both qualitative and quantitative methods.
For both candidates and interviewers, the interview process doesn't lend itself to the classic scientific method. We can't iterate over an interaction, and needs change. Deciding what to ask and who to interview can be a guessing game. As an interviewer, what kind of candidate do you really need? As a candidate, what kind of role do you really want? Having done more than 30 phone screens and technical challenges, I can define seven distinct types of Data Scientist interviews. I'll give examples of questions specifically relevant to assessing each aspect of a Data Scientist's skills, as well as discussing what's not being measured by the typical interview process.