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Case interview: basic business problem (if product X costs Capital One $4.00 per unit, with a $800 sunk cost, and we charge X amount of dollars along with a $10 annual fee, how many do we need to sell to break even, etc). Followed by a longer discussion of more complex problems that the situation might entail.
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Data Analyst

Interviewed at Capital One

3.4★
Nov 8, 2010

Case interview: basic business problem (if product X costs Capital One $4.00 per unit, with a $800 sunk cost, and we charge X amount of dollars along with a $10 annual fee, how many do we need to sell to break even, etc). Followed by a longer discussion of more complex problems that the situation might entail.

products sales +------------------+---------+ +------------------+---------+ | product_id | int |------->| product_id | int | | product_class_id | int | +---->| store_id | int | | brand_name | varchar | | +->| customer_id | int | | product_name | varchar | | | | promotion_id | int | | price | int | | | | store_sales | decimal | +------------------+---------+ | | | store_cost | decimal | | | | units_sold | decimal | | | | transaction_date | date | | | +------------------+---------+ | | stores | | customers +-------------------+---------+ | | +---------------------+---------+ | store_id | int |-+ +--| customer_id | int | | type | varchar | | first_name | varchar | | name | varchar | | last_name | varchar | | state | varchar | | state | varchar | | first_opened_date | datetime| | birthdate | date | | last_remodel_date | datetime| | education | varchar | | area_sqft | int | | gender | varchar | +-------------------+---------+ | date_account_opened | date | +---------------------+---------+ Question 1: What brands have an average price above $3 and contain at least 2 different products? Question 2: To improve sales, the marketing department runs various types of promotions. The marketing manager would like to analyze the effectiveness of these promotion campaigns. In particular, what percent of our sales transactions had a valid promotion applied? Question 3: We want to run a new promotion for our most successful category of products (we call these categories “product classes”). Can you find out what are the top 3 selling product classes by total sales? Question 4: We are considering running a promo across brands. We want to target customers who have bought products from two specific brands. Can you find out which customers have bought products from both the “Fort West" and the "Golden" brands?
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Data Engineer

Interviewed at Meta

3.6★
May 22, 2020

products sales +------------------+---------+ +------------------+---------+ | product_id | int |------->| product_id | int | | product_class_id | int | +---->| store_id | int | | brand_name | varchar | | +->| customer_id | int | | product_name | varchar | | | | promotion_id | int | | price | int | | | | store_sales | decimal | +------------------+---------+ | | | store_cost | decimal | | | | units_sold | decimal | | | | transaction_date | date | | | +------------------+---------+ | | stores | | customers +-------------------+---------+ | | +---------------------+---------+ | store_id | int |-+ +--| customer_id | int | | type | varchar | | first_name | varchar | | name | varchar | | last_name | varchar | | state | varchar | | state | varchar | | first_opened_date | datetime| | birthdate | date | | last_remodel_date | datetime| | education | varchar | | area_sqft | int | | gender | varchar | +-------------------+---------+ | date_account_opened | date | +---------------------+---------+ Question 1: What brands have an average price above $3 and contain at least 2 different products? Question 2: To improve sales, the marketing department runs various types of promotions. The marketing manager would like to analyze the effectiveness of these promotion campaigns. In particular, what percent of our sales transactions had a valid promotion applied? Question 3: We want to run a new promotion for our most successful category of products (we call these categories “product classes”). Can you find out what are the top 3 selling product classes by total sales? Question 4: We are considering running a promo across brands. We want to target customers who have bought products from two specific brands. Can you find out which customers have bought products from both the “Fort West" and the "Golden" brands?

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?

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