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Product Analyst Interview Questions

1

How do you determine risk with a client?

Open-ended

2

How do you present to leadership?

Open-ended

3

How do you measure success?

Open-ended

4

How do you stay organized?

Open-ended

5

How do you make recommendations?

Open-ended

6

I want to imagine you are the data expert on a project, how do you make sure everyone understands what you need from a data perspective?

Open-ended

7

Tell me about a time you did not achieve your goals, what happened and what did you learn from it?

Behavioral

8

Tell me about a time you had to create complex analysis to solve business needs?

Behavioral

9

Tell me about a time you optimized for your organization and it had tremendous success?

Behavioral

10

Tell me about a time your collaborative analysis yielded success?

Behavioral

11

How do you remove roadblocks?

Open-ended

12

Tell me about a time when you took something apart and rebuilt it?

Behavioral

13

Tell me about the most unique set of business requirements you ever worked with?

Behavioral

14

Tell me about a conflict you had with an internal partner and how you resolved it?

Behavioral

15

How do you identify trends?

Open-ended

16

Can you give me an example of when you�ve been able to see around the corner to meet your internal customer�s needs?

Behavioral

17

How do you foster strong relationships with the product team?

Open-ended

18

How many Google Homes will be sold in the US in 2020?

Open-ended

19

How would you make a Google product more profitable?

Open-ended

20

Tell me about a time you set a stretch goal and achieved it?

Behavioral

21

Tell me about the coolest dashboard you have implemented in your career?

Behavioral

22

What are the most important components of metrics reporting?

Open-ended

23

How do you build trust?

Open-ended

24

How do you define business requirements?

Open-ended

25

How do you connect the dots with data?

Open-ended

26

Tell me about a time that you identified an opportunity and how you got group buy-in to pursue it.

Behavioral

27

Tell me about a time when an employee gave you negative feedback.

Behavioral

28

Tell me about a time when someone changed their mind after you had already started leading a project. How did you handle it?

Behavioral

29

Tell me about a time when you gave an important piece of feedback to someone.

Behavioral

30

Tell me about a time when you got an under performing team member to improve their work.

Behavioral

31

Tell me about a time when you had a disagreement with your manager.

Behavioral

32

Tell me about a time when you were able to make a decision without having much data metrics in hand.

Behavioral

33

Tell me about a time where your analysis didn't yield the results you were expecting. What did you learn from the experience?

Behavioral

34

What is a Facebook product that you�d be interested in working on? How would you use analytics to improve it?

Open-ended

35

We�ve introduced this particular new friend recommendation feature that allows you to see degrees of separation. How should we determine whether to keep it or not?

Open-ended

36

Given data on Facebook members friending/defriending each other on Facebook, find out whether a given pair of members are currently friends.

Open-ended

37

Imagine Facebook has data on height and gender of our users. How would you prove whether men are taller than women?

Open-ended

38

Imagine we're looking at Facebook data divided by gender. What statistical methods would you use to verify that different genders have different levels of activity?

Open-ended

39

How would you test whether having more friends now increases the probability that a Facebook member is still an active user after 6 months?

Open-ended

40

Facebook has raters to rate ads: 80% are careful raters and rate 60% of the ads as good and 40% as bad, 20% are lazy raters and rate 100% ads as good. What is the probability that an ad is rated good? Given that 3 ads have been rated as good, what is the probability that they were rated by a lazy rater? Given that n ads have been rated as good, what is the probability that they were rated by a lazy rater?

Open-ended

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