How to Interview a Data Scientist
The O'Reilly Strata Conference brings together an incredible community of people working on big data. This year, I decided to do something different for my presentation. Rather than talk about science or technology, I addressed the practical problem of interviewing the candidates to build teams of data scientists.
My slides are below (and the video is on YouTube), but I'll summarize the take-aways:
1. Keep it real.
- Avoid whiteboard coding. Filter with FizzBuzz.
- Use real-world algorithms questions.
- Ask candidates to design your products.
2. No gotchas.
- Gotchas reduce the signal-to-noise ratio.
3. Maybe = no.
- Bad hires suck. Be conservative.
- Trust your team.
You can watch the video on Youtube or look at the slides below.
COO at Richardson Oliver Insights / Partner at ROL Group
11 å¹´Excellent thoughts on this challenging process.
Co-Founder & CTO @ Onwish
11 å¹´very good for candidates as well
Chief AI | Cyber Security | Officer | AI Advisory Board CapTechU | AI/ML/Quantum Computing | Chair | Board Member | Professor, Adjunct
12 å¹´This is well done..
Co-Founder, BondingAI.io
12 å¹´Also google "66 job interview questions for data scientists".
Principal Advisor Reduction, Technical Services Rio Tinto Atlantic|LSSBB|Leading Sustainable Corporation| Decision-Making|Process Optimization| NEBOSH H&S Leadership Excellence IWorking Across Cultures| RIOEXPERT|
12 å¹´I would rather say, the advice is great in the case of hiring an expert to solve a specific issue the company is encountering; it is a straightaway strategy to select the right person at the right place. It is less realistic in other cases; rather, it's quiet radical as methodology of recruitment. Recruiter needs to evaluate various skills of potential candidates. As human, give them some benefits of doubt, stress factor for example.