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Given the following data: Table: searches Columns: date STRING date of the search, search_id INT the unique identifier of each search, user_id INT the unique identifier of the searcher, age_group STRING ('<30', '30-50', '50+'), search_query STRING the text of the search query Sample Rows: date | search_id | user_id | age_group | search_query -------------------------------------------------------------------- '2020-01-01' | 101 | 9991 | '<30' | 'justin bieber' '2020-01-01' | 102 | 9991 | '<30' | 'menlo park' '2020-01-01' | 103 | 5555 | '30-50' | 'john' '2020-01-01' | 104 | 1234 | '50+' | 'funny cats' Table: search_results Columns: date STRING date of the search action, search_id INT the unique identifier of each search, result_id INT the unique identifier of the result, result_type STRING (page, event, group, person, post, etc.), clicked BOOLEAN did the user click on the result? Sample Rows: date | search_id | result_id | result_type | clicked -------------------------------------------------------------------- '2020-01-01' | 101 | 1001 | 'page' | TRUE '2020-01-01' | 101 | 1002 | 'event' | FALSE '2020-01-01' | 101 | 1003 | 'event' | FALSE '2020-01-01' | 101 | 1004 | 'group' | FALSE Over the last 7 days, how many users made more than 10 searches? You notice that the number of users that clicked on a search result about a Facebook Event increased 10% week-over-week. How would you investigate? How do you decide if this is a good thing or a bad thing? The Events team wants to up-rank Events such that they show up higher in Search. How would you determine if this is a good idea or not?
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Data Scientist

Interviewed at Meta

3.5★
Apr 23, 2021

Given the following data: Table: searches Columns: date STRING date of the search, search_id INT the unique identifier of each search, user_id INT the unique identifier of the searcher, age_group STRING ('<30', '30-50', '50+'), search_query STRING the text of the search query Sample Rows: date | search_id | user_id | age_group | search_query -------------------------------------------------------------------- '2020-01-01' | 101 | 9991 | '<30' | 'justin bieber' '2020-01-01' | 102 | 9991 | '<30' | 'menlo park' '2020-01-01' | 103 | 5555 | '30-50' | 'john' '2020-01-01' | 104 | 1234 | '50+' | 'funny cats' Table: search_results Columns: date STRING date of the search action, search_id INT the unique identifier of each search, result_id INT the unique identifier of the result, result_type STRING (page, event, group, person, post, etc.), clicked BOOLEAN did the user click on the result? Sample Rows: date | search_id | result_id | result_type | clicked -------------------------------------------------------------------- '2020-01-01' | 101 | 1001 | 'page' | TRUE '2020-01-01' | 101 | 1002 | 'event' | FALSE '2020-01-01' | 101 | 1003 | 'event' | FALSE '2020-01-01' | 101 | 1004 | 'group' | FALSE Over the last 7 days, how many users made more than 10 searches? You notice that the number of users that clicked on a search result about a Facebook Event increased 10% week-over-week. How would you investigate? How do you decide if this is a good thing or a bad thing? The Events team wants to up-rank Events such that they show up higher in Search. How would you determine if this is a good idea or not?

The company developed a new feature and perform A/B test. Here is the result Comments +5% Likes -10% Timespent +1% All else neutral How would you decide to whether putting into product based on the A/B test result? Any ideas?
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Data Scientist

Interviewed at Meta

3.5★
Jun 8, 2017

The company developed a new feature and perform A/B test. Here is the result Comments +5% Likes -10% Timespent +1% All else neutral How would you decide to whether putting into product based on the A/B test result? Any ideas?

SQL part1 Question # 1 : you have the following table - User_id , action (post, edit, cancel) , date == > what is the post rate Question # 2 : you have also the following table (active users) - User_id , country , active , date == > What is the average post rate for yesterday for all active users by country
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Data Scientist

Interviewed at Meta

3.5★
Aug 7, 2019

SQL part1 Question # 1 : you have the following table - User_id , action (post, edit, cancel) , date == > what is the post rate Question # 2 : you have also the following table (active users) - User_id , country , active , date == > What is the average post rate for yesterday for all active users by country

We have a table called ad_accounts(account_id, date, status). Status can be active/closed/fraud. A) what percent of active accounts are fraud? B) How many accounts became fraud today for the first time? C) What would be the financial impact of letting fraud accounts become active (how would you approach this question)?
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Data Scientist, Analytics

Interviewed at Meta

3.5★
Mar 6, 2019

We have a table called ad_accounts(account_id, date, status). Status can be active/closed/fraud. A) what percent of active accounts are fraud? B) How many accounts became fraud today for the first time? C) What would be the financial impact of letting fraud accounts become active (how would you approach this question)?

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