DoorDash Data Scientist Mock Interview
Practice 30 DoorDash Data Scientist interview questions covering experimentation, marketplace metrics, and product analytics.
Question 24 of 30
In your opinion, is mean square error a good or bad measure of model performance?
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William Swansen has worked in the employment assistance realm since 2007. He is an author, job search strategist, and career advisor who helps individuals worldwide and in various professions to find their ideal careers.
As with any career or profession, the techniques and methodologies used may differ between individuals. Interviewers at Doordash will ask you questions similar to this one to learn more about your expertise and how you go about doing your job. They also are interested in your opinion on specific topics, some of which may be controversial. When you answer this type of question, it is best to give them your honest opinion. Trying to please the interviewer may work during the interview, but it may cause issues once you are hired.
William Swansen has worked in the employment assistance realm since 2007. He is an author, job search strategist, and career advisor who helps individuals worldwide and in various professions to find their ideal careers.
"I believe that the mean square error, or MSE, is a flawed measure of a decision model's performance. The problem of using MSE for this purpose is that it weighs larger errors more than smaller ones. This results in applying emphasis on the large deviations in the data. I prefer to use mean absolute deviation, or MAE, which is a more robust model and provides a more accurate measure of a model's performance."
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