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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

3.6★
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

3.6★
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?

There are 50 cards of 5 different colors. It comprises of 10 Red cards, 10 blue cards, 10 orange cards, 10 green cards and 10 yellow cards. Each color will have the cards numbered between 1 to10. You pick 2 cards at random. What is the probability that they are not of same color and not of same number.
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Data Scientist

Interviewed at Meta

3.6★
Jul 17, 2016

There are 50 cards of 5 different colors. It comprises of 10 Red cards, 10 blue cards, 10 orange cards, 10 green cards and 10 yellow cards. Each color will have the cards numbered between 1 to10. You pick 2 cards at random. What is the probability that they are not of same color and not of same number.

There's a game where you are given two fair six-sided dice and asked to roll. If the sum of the values on the dice equals seven, then you win $21. However, you must pay $5 to play each time you roll both dice. Do you play this game? And in follow-up: What is the probability of making money from this game?
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Data Scientist

Interviewed at Meta

3.6★
Nov 24, 2016

There's a game where you are given two fair six-sided dice and asked to roll. If the sum of the values on the dice equals seven, then you win $21. However, you must pay $5 to play each time you roll both dice. Do you play this game? And in follow-up: What is the probability of making money from this game?

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?
avatar

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?

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