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SQL question: given a table of interaction between users (user_a | user_b | day), find number of users who had more than 5 interactions yesterday (assume there is only one unique interaction between a pair of users per day). Product Question: A user satisfaction survey was conducted for two groups of facebook users (each with 50 k sample size). Group1: who had enabled certain login security features Group 2: who had not enabled these security features. It was found that user satisfaction with group1 was 30% lower than with group 2. Why do you think so? Comment on how the survey was conducted?
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Data Scientist

Interviewed at Meta

3.6★
May 11, 2018

SQL question: given a table of interaction between users (user_a | user_b | day), find number of users who had more than 5 interactions yesterday (assume there is only one unique interaction between a pair of users per day). Product Question: A user satisfaction survey was conducted for two groups of facebook users (each with 50 k sample size). Group1: who had enabled certain login security features Group 2: who had not enabled these security features. It was found that user satisfaction with group1 was 30% lower than with group 2. Why do you think so? Comment on how the survey was conducted?

Given a table with columns country (with two-letter country abbreviation), count of requests sent, percentage of requests sent failed, condense down to this data grouped by country: country (one row per country), total count of requests sent, total count of requests sent failed.
avatar

Data Scientist

Interviewed at Meta

3.6★
Apr 29, 2019

Given a table with columns country (with two-letter country abbreviation), count of requests sent, percentage of requests sent failed, condense down to this data grouped by country: country (one row per country), total count of requests sent, total count of requests sent failed.

Given a multi-step product feature, write SQL to see how well this feature is doing (loading times, step completion %). Then use Python to constantly update average step time as new values stream in, given that there are too many to store in memory.
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Data Engineer

Interviewed at Meta

3.6★
Apr 30, 2018

Given a multi-step product feature, write SQL to see how well this feature is doing (loading times, step completion %). Then use Python to constantly update average step time as new values stream in, given that there are too many to store in memory.

SQL: 1. Percentage increase in revenue compared to promoted and non-promoted products. 2. Products classes that has the highest transactions 3. Count of Customers who bought 2 items type (A,B) 4. Don't remember Python: 1. Average length of letters to words. 2. Parse an ip address (This is a favourite FB question) 3. [[A],[A,B],[A,C],[B,D],[C,A]] -- Find the alphabet with highest neighbors? -- (Wasnt able to solve because of time limit but the interviewer was like I get what I want to convey.. I gave her an algo of what I would I have done)
avatar

Data Engineer

Interviewed at Meta

3.6★
Sep 21, 2018

SQL: 1. Percentage increase in revenue compared to promoted and non-promoted products. 2. Products classes that has the highest transactions 3. Count of Customers who bought 2 items type (A,B) 4. Don't remember Python: 1. Average length of letters to words. 2. Parse an ip address (This is a favourite FB question) 3. [[A],[A,B],[A,C],[B,D],[C,A]] -- Find the alphabet with highest neighbors? -- (Wasnt able to solve because of time limit but the interviewer was like I get what I want to convey.. I gave her an algo of what I would I have done)

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