> You ask for writing and descriptions on why a model was chosen, why features matters - are you grading this automatically? That would be a feat.
Grading is apparently not automatic, which is good as I am not a fan of the Kaggle approach in this demo.
> The task is waaay to easy (even if you do believe there is a market for identifying people who can predict well)
You'd be very surprised about how candidates can respond to these types of questions!
> Python is overly limited. Why not SQL or R?
The full product allows Python, R, and Julia, with popular packages preinstalled for Python/R.
- We are not automatically grading it. We have learned that in the past that trying to automatically grade candidates on such challenges biases their approach, which breaks the point of a good data science challenge.
- that's good to know. we are not really focusing on the final outcome but how creatively a candidate can go about the problem. the dataset allows for some good amount of creativity.
- Ah. can you elaborate what you mean by overly limited? We do support R.
Tools to hire data scientists and going to continually fail until they realize that the interesting, hard part of being a data scientist is closer akin to a business lead (which can't really be tested in 60 minutes).
Concrete feedback:
- You ask for writing and descriptions on why a model was chosen, why features matters - are you grading this automatically? That would be a feat.
- The task is waaay to easy (even if you do believe there is a market for identifying people who can predict well).
- Python is overly limited. Why not SQL or R?