DoorDash Data Scientist Mock Interview (Commentary)

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This is a snippet of a mock interview based on a product DS role in DoorDash. Interviewer commentaries are provided to help candidates understand how to prepare for technical interviews.

[@nanfengbb]

Great video. One little suggestion, the way Q3 was worded "How do you calculate the type I error and type II error" is kind of misleading. To my understanding, type I error and type II error are not "calculated"; they are predetermined when you design an experiment. alpha is usually set at 0.05, hence type I error 0.05; power is usually set at 0.8, hence type II error 0.2. There is really not much "calculation" involved. Correct me if I am wrong.

[@yiruzuoriliangzhu]

I think u can calculate them - what is predetermined is *threshold/cutoff* of prob of type I or II error.

[@yeyunhuang143]

Thank you Dan! it's quite helpful!!

[@ravitanwar9537]

keep em coming!

[@sahilsharma-hj4gq]

can you recommend some resource from where I should learn statistics and probability? Thank you for this.

[@DataInterview]

Back when I was a student and an entry-level data scientist, I used the following resources: ISLR book, Probability by Jim Pitman, and A/B Testing course on Udacity. Hope these help!

[@richardcyc]

Thank you Dan! Your content is very helpful. I learned a lot from your comments about the answers.

[@DataInterview]

Thank you! I created this video based on my personal experience as a DS interview candidate a few years ago. I always felt that the interview process in DS/MLE is a black-box, and I figured demystifying the process can help others succeed! More content will come soon. I just need to find the bandwidth :) -- Dan

[@horoshuhin]

@@DataInterview thank you for your comments. it paints a bigger picture of the interview process. can't wait for more videos while i'm brushing over the concepts in this video:). keep it up Dan!!!

[@siyanhu]

Yeah the type I & II question sounds misleading to me too. it is actually asking candidates to explain in details what alpha and beta mean in practical cases. (instead of calculating)

[@TheJason143]

Hey Dan, love your content! do you have any resources you recommend specifically on statistical concepts? About statistical tests, when to use them, etc?

[@DataInterview]

Thanks Jason, I have a formal education in statistics so I can only convey based on my personal experience. Here's one book I recommend on learning statistical concepts: "Mathematical Statistics with Applications by Dennis Wackerly". In terms of learning about statistical tests, here's GitHub book that could be helpful for you: crumplab.github.io/statistics/factorial-anova.html

[@horoshuhin]

@@DataInterview nice! thanks for the reading recommendations.

[@How2hit]

Thanks man keep up!

[@TheValithan]

Audio of the candidate was awful, couldnt listen to.

[@hamisaoumellal8742]

please upload more interview videos like this! Thank you!