Pinterest | Data Analyst Interview | Reject
Summary
I interviewed for a Data Analyst role at Pinterest, which involved a phone screen, a writing contest, and a coding interview focused on SQL and R. Ultimately, I was rejected for the position.
Full Experience
My interview process for the Data Analyst role at Pinterest began with a Phone Screening. During this round, I was asked to articulate my reasons for wanting to work at Pinterest and explain why I believed I would be a good fit for the company.
Following that, I participated in a Writing Contest. For this, I had been previously sent an article on Recommendation Systems. My task was to write a one-page article, intended for hypothetical non-technical stakeholders at Netflix, explaining what a recommendation system is and outlining the benefits of implementing such a system.
The final stage was a Coding Interview. This round featured two SQL questions and one R data manipulation question. The SQL questions were quite detailed, involving identifying non-spammer requests and calculating month-over-month download growth. Despite my efforts, I received a rejection after completing all the interview rounds.
Interview Questions (5)
Explain your motivation for wanting to work at Pinterest.
Describe why you believe you would be a good fit for Pinterest.
Read an article on Recommendation Systems (provided by the company) and write a one-page article explaining to non-technical stakeholders at Netflix (hypothetically) what a recommendation system is and why using such a system would be useful for them.
Given two tables, a 'Spam Account Table' and a 'Spam Request Table', identify all requests made by non-spammers.
Input Table Schema (Spam Request Table):Sending UserID | Receiving UserID | Date | IsAccept12 | 1 | 12.1.2019 | 113 | 3 | 12.1.2019 | 014 | 3 | 12.1.2019 | 1
Input Table Schema (Spam Account Table):UserID | isSpam12 | 103 | 102 | 0
Given a table with 'PhoneType', 'Month', and 'DownloadCount', add a new column calculating the month-over-month growth rate in downloads.
Input:PhoneType | Month | DownloadCountAndroid | Jan | 1000Android | Feb | 1001Android | Mar | 1002
Output Desired:PhoneType | Month | DownloadCount | MoMAndroid | Jan | 1000 | 0Android | Feb | 1001 | 1Android | Mar | 1012 | 13