10 Product Sense Interview Questions for data scientist

Last updated: Nov. 9, 2023
3 mins read
Leon Wei
Leon

10 common data scientist product sense interview questions.

If you are preparing for a data scientist job interview and want to practice mock interviews with FAANG hiring managers, feel free to use our coaching service.

If you have questions, or want to share your answers, discuss in our forum.


1. Ads Revenue

Our ads revenue dropped suddenly. What should we do? How do we figure out the cause, and how would you explain this to the senior management team?

 

2. Marketplace

i) How do you measure our newly launched our second hand product marketplace health? (think about Craigslist)

ii) Would you adjust your measurements based on other factors such as product group size or the age of the group?

 

3. Comment

Recently, customers comment switched to a hierarchical structure (similar to Reddit). So how do we know if it is successful?

 

4. Parents on social media

What kind of impact when a teenager's parents join the social media network?

Follow up questions:

1) AB test: what is the potential issue with randomly selecting one Group having parents and the other groups don't?

2) How to determine a pair of parent-children relationships?

 

5. Fake news

  1. How do you estimate the volume of fake news, assuming 
  2. How do you measure the impact of fake news
  3. How do you build a fake news prediction model, what features will you use, and evaluate the model performance. 
  4. How do you improve the model performance, especially when not catching enough fake news?

 

6. People you may know 

1. If you are the data scientist working on this people you may know feature, how would you build such a recommendation model?

2. How do you evaluate its performance?

 

7. UI change

When you swipe the newsfeed on your mobile phone, you will find that a post occupies almost the entire screen of your mobile phone, including the post's primary content, the comments left by others, a comment box, and so on. 

Now we plan to reduce the size of each post so that one mobile phone screen can fit more posts.

  1.  How do we evaluate its impact? What metrics will you use, why?
  2.  After the launch, we found that the US ads revenue has increased, but Japan has decreased. What should we do?
  3. How do we decide how often we insert an ad inside people's newsfeeds?

 

8. Notifications

  1. How do we measure the quality of the notifications from our food delivery app?
  2.  How do we improve the notification delivery?
  3.  How do we decide the maximum number of notifications people receive per day?

 

9. User account

Background: a email service provider made a new feature that allows users to easily switch to a different account by clicking on a switch button and selecting a new account without logging out and signing in again.

  1. How do we determine if multiple accounts belong to the same user?
  2. How do you measure the success of this new feature?
  3. After the new feature was launched, we found that the average number of accounts per user has increased, but the average time people spent on the email account didn't. Why?
  4. Who are the users that are going to like this feature? And who is not?

 

10. Restaurant recommendation

We are going to add a new feature that recommends nearby restaurants when users use our map app.

i) What kind of impact will this feature bring to the customers?

ii) How do you build the model? What kind of features will you use? How do we evaluate your model performance?

iii) How do we measure the success of this feature?

iv) What do you think are the difference between restaurant recommendations vs. people you may know recommendations?


10 common data scientist product sense interview questions.

If you are preparing for a data scientist job interview and want to practice mock interviews with FAANG hiring managers, feel free to use our coaching service.

If you have questions, or want to share your answers, discuss in our forum.



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