Project-based Data Science Interview Questions: How to Explain Your Projects with Confidence!

How to Talk About Previous Data Science Projects in Interviews | Project-based Questions | Data Science Interview

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Contents of this video:
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00:00 How to structure your answer?
00:55 Things to pay attention to
01:32 Overview: context and impact
3:35 Challenges
05:01 Why talk about challenges?
06:41 Interesting finding
07:34 Why not using the S.t.a.r. method?
10:31 Summary

[neopineaapl]

Went to a couple interviews with STAR method, I found it difficult to impress the interviewers. Your method makes so much sense that I will definitely try it out next time. This is a hidden gem channel; it deserves a million views.

[thudang]

Hi Emma, I just can't thank life enough to let me stumble upon your channel. I've been binge-watching your videos to prep for my screening interview. The videos just bring so much clarity to the topics that I'm so afraid of talking about, such as DS topics like A/B testing and behavioral topics. I'm so so thankful and I look forward to your great great content every week!

[jeoffleonora]

Oops, just realized how bad it was when I presented my project. Huge thanks to Emma! Otherwise I will never know my mistakes.

[jessieshao]

Thanks for the video! I basically live with these videos recently.

[zbear]

You saved me from using the STAR method! Thanks a bunch! I'll drop by again to comment on whether or not I got my internship!

[kangxinwang]

Hi Emma, just wanted to say thank you for providing such good contents, I have onsite interviews next week and these vids are life saver ;)

[Amanda-znsu]

super helpful as always! thank you so much!!

[mikemihay]

Great video! Keep up with the good work!

[AmanSingh-xklv]

This is an interesting way to do it, thanks!

Thank you for the enlightening video Emma, it always happens when I am describing my projects, I forget to structure the content. And although I tell everything it's sounds very random to the interviewer. I will use the STAR method and hopefully after enough practise get better at it.

[lydiamai]

Thank you Emma for your practical video.

[guilad]

Thank you, this has been eye opening.

[jiayiwu]

8:40 Almost think I am the friend you talked about in this funny Wish I saw this video earlier!!! The best video for DS about project description!! Thank you!!

[yuewang]

It is super helpful! Thanks for the video!!!

[nien-thingchiang]

Thank you so much for your sharing! It is really helpful :)

[EvanZamir]

Thanks so much for these videos. It helped me get past the screening interview for FB!

[haitingyou]

Thanks for sharing, your video really helps me find out the reason why I failed the interview again and again.

[sinnottboy]

I was preparing some notes for a potential question like this before watching your video. After watching this I’m completely revising my answer. Your videos bring so much clarity to each topic you cover and I’m really feeling good about my upcoming onsite thanks to you! Keep up the good work!

[kqqvmvy]

Great insight, especially the parts discussing why STAR does not work

[wayneshih]

Very insightful!
agree with that as a data scientist you need to present the projects and yourself in an efficient way, and not just follow the STAR method.