The hiring process leaves a lot to be desired. A candidate is judged fit or unfit for a position with only about one day of interaction. These interactions are split up amongst a handful of people, so each person has about an hour to say if they want to spend more waking time with this person then they do their own family.
First, you must agree on the interviewing basics. Here’s the basic advice for all tech hiring that we use at DesignMind:
Hiring a Data Scientist: Interviewing Basics
1. You should have a mid-size group of people interviewing the candidate. Five to eight is a good range of formal interviewers. There can be more if the candidate goes out to lunch with a group, or if you do some pair interviewing. But after 6-8 interview sessions, almost any candidate will burn out.
2. A range of people need to interview the candidate. Having people who do similar work is definitely necessary, but people outside of the core group should also be on he interviewing team. Knowing if a candidate can talk to people of different backgrounds is a requirement if this person will be on cross-functional teams. Also, knowing how a candidate will interact with a perceived “subordinate” is great insight on how that person works inside of an organization.
3. Interview feedback should happen within an interview team pow-wow within a day of the interview. First round of responses should be “yes”, “no”, or “maybe”, where:
- No means no
- Maybe means no
- Yes means maybe
There can be mitigating circumstances where a maybe can be turned into a yes. But if not, you need to pass on the candidate.
4. If the hiring team gives the candidate a yes, it is time to check references. If there are any dubious responses, you need to dig into them and find the reason. Often, finding someone in your extended network who has worked with this person is a great way to get an honest, unbiased answer.
5. Last, and most important, the candidate is interviewing you and your company during the interview process. Don’t forget to sell your company and its people during the interview.
DesignMind’s Data Science division specializes in data mining, data modeling, and artificial intelligence.