It's easy to build data practice ethics into your data science interviewing process. Add a few questions mixed in with your standard tech interview, and pay attention to the responses.
For example:
For example:
1) You're working on a model for consumer access to a financial service. Race is a significant feature in your model, but you can't use race. What do you do?
Wrong: I use zip code, because that correlates with race.
Right: I remove race as a factor and accept lower accuracy.
Wrong: I use zip code, because that correlates with race.
Right: I remove race as a factor and accept lower accuracy.
2) You're asked to use network traffic data to offer loans to small businesses. It turns out that the available data doesn't rigorously inform credit risk. What do you do?
Wrong: I use the model anyway. After all, it's selling.
Right: I approach the business with my concerns.
Wrong: I use the model anyway. After all, it's selling.
Right: I approach the business with my concerns.
These are both fictionalized questions drawn from real scenarios I have seen "in the wild". They are not hypothetical.
The first one addresses the technical approach, the second one the business approach.
Please do consider adding a question like this to your interviews. 🙏🏻
The first one addresses the technical approach, the second one the business approach.
Please do consider adding a question like this to your interviews. 🙏🏻
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