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Finicity Interview Questions

Finicity Interview Guides

Data Structures & Algorithms

Given two sorted lists, write a function to merge them into one sorted list.

Merge Sorted Lists

Find the missing integer from a array of consequtive integers

Find the Missing Number

String Shift

Minimum Change

Given a list of integers, and an integer N, write a function to find all combinations that sum to the value N.

Sum to N

Select the 2nd highest salary in the engineering department

2nd Highest Salary

Write a query that returns all neighborhoods that have 0 users.

Empty Neighborhoods

Closest SAT Scores

Rolling Bank Transactions

Paired Products

Machine Learning

Encoding Categorical Features

Coefficients of Logistic Regression

Bank Fraud Model

Lasso vs Ridge

Rebalancing outcome probabilities for a classifier on imbalanced data.

Rebalance Probabilities

A/B Testing

Experiment Validity

Button AB Test

Network Experiment Design

Green Dot

Write a SQL query to find the average number of right swipes for different ranking algorithms.

Swipe Precision

Business Case

New Partner Card

Declining Applicants

Delivery Assignments

For e-commerce product growth via Facebook Ads, would you opt for a 90-day payment with a 6% fee or a 45-day payment with a 3% fee, and why?

Cashflow Interest Projection

Apartment Pricing

We’re given two tables, a <code>users</code> table with demographic information and the neighborhood they live in and a <code>neighborhoods</code> table.

Write a query that returns all neighborhoods that have 0 users. 

Example:

Input:

<code>users</code> table

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>neighborhood_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
<code>neighborhoods</code> table

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>city_id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>

Write a SQL query to select the 2nd highest salary in the engineering department.

Note: If more than one person shares the highest salary, the query should select the next highest salary.

Example:

Input:

<code>employees</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>first_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>last_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>salary</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>department_id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>departments</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>salary</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Given two sorted lists, write a function to merge them into one sorted list.

Bonus: What’s the time complexity?

Example:

Input:

<pre tabindex="0" class="chroma"><code>list1 = [1,2,5]
list2 = [2,4,6]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def merge_list(list1,list2) -&gt; [1,2,2,4,5,6]
</code></pre>

You have two sorted lists, one with m elements and one with n elements. What would be the time complexity of merging the two lists via merge sort?

You have two sorted lists, one with m elements and one with n elements. What would be the time complexity of merging the two lists via merge sort? 

Merging Lists Complexity

Given the <code>employees</code> and <code>departments</code> table, write a query to get the top 3 highest employee salaries by department. If the department contains less that 3 employees, the top 2 or the top 1 highest salaries should be listed (assume that each department has at least 1 employee). 

Note: The output should include the full name of the employee in one column, the department name, and the salary. The output should be sorted by department name in ascending order and salary in descending order. 

Example:

Input:

<code>employees</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>first_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>last_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>salary</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>department_id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>departments</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>employee_nam</code>e</td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>department_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>salary</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Get the top 3 highest employee salaries by department

Top Three Salaries

You have an array of integers, <code>nums</code> of length <code>n</code> spanning <code>0</code> to <code>n</code> with one missing. Write a function <code>missing_number</code> that returns the missing number in the array.

Note: Complexity of \(O(n)\) required.

Example:

Input:

<pre tabindex="0" class="chroma"><code>nums = [0,1,2,4,5] 
missing_number(nums) -&gt; 3
</code></pre>

We’re given a table of bank transactions with three columns, <code>user_id</code>, a deposit or withdrawal value (determined if the value is positive or negative), and <code>created_at</code> time for each transaction.

Write a query to get the total three-day rolling average for deposits by day.

Note: Please use the format <code>&#39;%Y-%m-%d&#39;</code> for the date in the outout

Example:

Input:

<code>bank_transactions</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>transaction_value</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>dt</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>rolling_three_day</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>

Given a table of students and their SAT test scores, write a query to return the two students with the closest test scores with the score difference.

If there are multiple students with the same minimum score difference, select the student name combination that is higher in the alphabet. 

Example:

Input:

<code>scores</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>student</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>score</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>one_student</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>other_student</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>score_diff</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Given an integer <code>N</code>, write a function that returns a list of all of the prime numbers up to <code>N</code>.

Note: Return an empty list there are no prime numbers less than or equal to <code>N</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code>N = 3
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def prime_numbers(N) -&gt; [2,3]
</code></pre>

Given an integer N, write a function that returns all of the prime numbers up to N

Prime to N

Given a table of bank transactions with columns <code>id</code>, <code>transaction_value</code>, and <code>created_at</code> representing the date and time for each transaction, write a query to get the last transaction for each day.

The output should include the id of the transaction, datetime of the transaction, and the transaction amount. Order the transactions by datetime.

Example:

Input:

<code>bank_transactions</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>transaction_value</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>transaction_value</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Last Transaction

Let’s say that your company is running a standard control and variant AB test on a feature to increase conversion rates on the landing page. The PM checks the results and finds a .04 p-value.

How would you assess the validity of the result?

Let’s say we have two tables, <code>transactions</code> and <code>products</code>. Hypothetically the <code>transactions</code> table consists of over a billion rows of purchases bought by users.

We are trying to find paired products that are often purchased together by the same user, such as wine and bottle openers, chips and beer, etc..

Write a query to find the top five paired products and their names.

Notes:
 For the purposes of satisfying the test case, p2 should be the item that comes first in the alphabet.
 The <code>qty</code> column represents paired products count

Example:

Input:

<code>transactions</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>product_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>quantity</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>products</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>price</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>p1</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>p2</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>qty</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Let’s say you work at Costco. Costco has a database with two tables. The first is <code>users</code> composed of user information, including their registration date, and the second is <code>purchases</code> that has the entire item purchase history (if any) for those users.

Write a query to get the total amount spent on each item in the ‘purchases’ table by users that registered in 2022.

Example:

Input:

<code>users</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>user_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>registration_date</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
<code>purchases</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>order_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>item</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>price</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>purchase_date</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>item</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>total_amount_spent</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>

Total Spent on Products

Given a list of strings of letters from <code>a</code> to <code>z</code>, create a function, <code>sum_alphabet</code>, that returns a list of the alphabet sum of each word in the string.

The alphabet sum is the sum of the ordinal position of each of the string’s letters in the standard English alphabet ordering. So, the letter <code>a</code> will have a value of <code>1</code>, <code>z</code> will have a value of <code>26</code>, and so on.

As an example of the alphabet sum of a string, the string <code>sport</code> will have an <code>alphabet sum of 19 + 16 + 15 + 18 + 20 = 88</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code>words = [&#34;sport&#34; , &#34;good&#34; , &#34;bad&#34;]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def sum_alphabet(words) -&gt; [88 , 41 , 7]
</code></pre>

Alphabet Sum

Assume you have a logistic model that is heavily weighted on one variable and that one variable has sample data like 50.00, 100.00, 40.00, etc….

Next let’s assume that there was a data quality issue with that variable and an unknown number of values removed the decimal point. For example 100.00 turned into 10000.

Would the model still be valid? Why or why not? How would you fix the model?

In predicting Airbnb booking prices with a dataset containing thousands of diverse features, which regression model could potentially perform better?

In predicting Airbnb booking prices with a dataset containing thousands of diverse features, which regression model could potentially perform better?

Variable Error

You have a table containing information about the time that employees have worked on a project.

Write a query to find how many unique calendar days each employee worked. Order your query by the <code>employee_id</code>.

Example:

An employee worked on two projects, and recorded their time like this:

<table>
<thead>
<tr>
<th>employee_id</th>
<th>project_id</th>
<th>start_date</th>
<th>end_date</th>
</tr>
</thead>

<tbody>
<tr>
<td>1	</td>
<td>1</td>
<td>2024-01-01</td>
<td>2024-01-06</td>
</tr>

<tr>
<td>1	</td>
<td>2</td>
<td>2024-01-03</td>
<td>2024-01-07</td>
</tr>
</tbody>
</table>
The number of unique calendar days is therefore 7.

<h3>Schema</h3>

Input:

<code>projects</code> table

<table>
<thead>
<tr>
<th>Columns	</th>
<th>	Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>employee_id</code>	</td>
<td>	INTEGER	</td>
</tr>

<tr>
<td><code>project_id</code>	</td>
<td>	INTEGER	</td>
</tr>

<tr>
<td><code>start_date</code>	</td>
<td>	DATE	</td>
</tr>

<tr>
<td><code>end_date</code>	</td>
<td>	DATE	</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Columns	</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>employee_id</code>	</td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>unique_days_worked</code>	</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

<h3>Example</h3>

Input:

<code>projects</code> table

<table>
<thead>
<tr>
<th>employee_id</th>
<th>project_id</th>
<th>start_date</th>
<th>end_date</th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>1</td>
<td>2024-01-01</td>
<td>2024-01-15</td>
</tr>

<tr>
<td>1</td>
<td>1</td>
<td>2024-01-21</td>
<td>2024-01-31</td>
</tr>

<tr>
<td>1</td>
<td>2</td>
<td>2024-01-25</td>
<td>2024-02-28</td>
</tr>

<tr>
<td>2</td>
<td>3</td>
<td>2024-01-01</td>
<td>2024-01-31</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>employee_id</th>
<th>unique_days_worked</th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>54</td>
</tr>

<tr>
<td>2</td>
<td>31</td>
</tr>
</tbody>
</table>

Unique Work Days

Let’s say that you work at a bank that wants to build a model to detect fraud on the platform.

The bank wants to implement a text messaging service in addition that will text customers when the model detects a fraudulent transaction in order for the customer to approve or deny the transaction with a text response.

How would we build this model?

Let’s say that you work at a bank that wants to build a model to detect fraud on the platform.

The bank wants to implement a text messaging service that will text customers when the model detects a fraudulent transaction in order for the customer to approve or deny the transaction with a text response.

Which statement is true?

Let's say that you work at a bank that wants to build a model to detect fraud on the platform.

The bank wants to implement a text messaging service that will text customers when the model detects a fraudulent transaction in order for the customer to approve or deny the transaction with a text response.

Which statement is true?

There are two tables. One table is called <code>swipes</code> that holds a row for every Tinder swipe and contains a boolean column that determines if the swipe was a right or left swipe called <code>is_right_swipe</code>. The second is a table named <code>variants</code> that determines which user has which variant of an AB test.

Write a SQL query to output the average number of right swipes for two different variants of a feed ranking algorithm by comparing users that have swiped 10, 50, and 100 swipes in a <code>feed_change</code> experiment.

Note: Users have to have swiped at least 10 times to be included in the subset of users to analyze the mean number of right swipes.

Example:

Input:

<code>variants</code> table

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>experiment</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>variant</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>swipes</code> table

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>swiped_user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>is_right_swipe</code></td>
<td>BOOLEAN</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>variant</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>mean_right_swipes</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>swipe_threshold</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>num_users</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Given two strings <code>A</code> and <code>B</code>, write a function <code>can_shift</code> to return whether or not <code>A</code> can be shifted some number of places to get <code>B</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code>A = &#39;abcde&#39;
B = &#39;cdeab&#39;
can_shift(A, B) == True

A = &#39;abc&#39;
B = &#39;acb&#39;
can_shift(A, B) == False
</code></pre>

Write a query to show the number of users, number of transactions placed, and total order amount per month in the year 2020. Assume that we are only interested in the monthly reports for a single year (January-December).

Example:

Input:

<code>transactions</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>product_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>quantity</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>products</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>price</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>
<code>users</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>sex</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>month</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>num_customers</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>num_orders</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>order_amt</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Monthly Customer Report

You are given two rectangles <code>a</code> and <code>b</code> each defined by four ordered pairs denoting their corners on the <code>x</code>, <code>y</code> plane. Write a function <code>rectangle_overlap</code> to determine whether or not they overlap. Return <code>True</code> if so, and <code>False</code> otherwise.

Note: If the two rectangles border one another, or share a corner like two diagonally adjacent positions on a chessboard, they are said to overlap.

Note: The lists of ordered pairs are in no particular order. The first entry in list <code>a</code> could be the top left corner while the first in list <code>b</code> is the bottom right.

Example:

Input:

<pre tabindex="0" class="chroma"><code>
a = [(-3,5), (-3,2),(0,5),(0,2)]
b = [(-1,4), (3,4), (3,1), (-1,1)]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def rectangle_overlap(a, b) -&gt; True
</code></pre>

As point <code>(0,2)</code> is fully contained in rectangle <code>b</code> and point <code>(-1,4)</code> is fully contained in a rectangle <code>a</code>.

Write a function to determine whether or not two rectangles overlap.

Rectangle Overlap

Write a function <code>minimum_change</code> to find the minimum number of coins that make up the given amount of change <code>cents</code>. Assume we only have coins of value 1, 5, 10, and 25 cents.

Example:

Input:

<pre tabindex="0" class="chroma"><code>cents = 73
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def minimum_change(cents) -&gt; 7
#(25 + 25 + 10 + 10 + 1 + 1 + 1)
</code></pre>

How would you explain what a p-value is to someone who is not technical?

What does a p-value in a statistical test represent?

What does a p-value in a statistical test represent?

P-value to a Layman I

In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?

In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?

P-value to a Layman II

P-value to a Layman

Statistics

Given the <code>transactions</code> table below, write a query that finds the third purchase of every user.

Note: Sort the results by the <code>user_id</code> in ascending order. If a user purchases two products at the same time, the lower <code>id</code> field is used to determine which is the first purchase.

Example:

Input:

<code>transactions</code> table

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>product_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>quantity</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>product_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>quantity</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Third Purchase

Given a string, find the first non-repeating character in it and return its index. If it doesn’t exist, return -1.

Example questions:

Consider a string where all characters are lowercase alphabets.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>s = &#39;helloworld&#39;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>first_uniq_char(s) -&gt; 0
</code></pre>

In the string ‘helloworld’, the first non-repeating character is ‘h’, which is at index 0.

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>s = &#39;concussion&#39;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>first_uniq_char(s) -&gt; 4
</code></pre>

In the string ‘concussion’, the first non-repeating character is ‘u’, which is at index 4.

This problem involves finding the first non-repeating character in a given string. The solution involves iterating over the string and keeping track of the frequency of each character. The first character that has a frequency of 1 is the first non-repeating character.

Find the First Non-Repeating Character in a String

Given a list of <code>integers</code>, and an integer <code>N</code>, write a function <code>sum_to_n</code> to find all combinations that sum to the value <code>N</code>.

Example: 

Input:

<pre tabindex="0" class="chroma"><code>integers = [2,3,5]
N = 8
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def sum_to_n(integers, N) -&gt;
 [
 [2,2,2,2],
 [2,3,3],
 [3,5]
]
</code></pre>

You’re a data scientist at Meta working on a feature that helps users discover trending books and understand borrowing behavior across the platform’s digital library.

Every time a user borrows a book, the system logs a <code>borrowed_at</code> timestamp and a <code>returned_at</code> timestamp. The team wants to measure how long books are typically kept, while also flagging which books have large inventories.

Write a SQL query to compute the following metrics for each book:

<ol>
<li><code>avg_borrow_duration_days</code>: average borrowing duration in days (rounded to 2 decimals)</li>
<li><code>has_over_10_copies</code>: <code>&#39;Yes&#39;</code> if the book has more than 10 copies available, otherwise <code>&#39;No&#39;</code></li>
</ol>

Only include completed borrows where <code>returned_at</code> is not NULL.

Sort results by <code>avg_borrow_duration_days</code> DESC, then by <code>book_id</code> ASC.

Note: Every book that has at least one completed borrow should appear in the output.

<h3>Schema</h3>

Input

<code>books</code> Table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td>book_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>title</td>
<td>VARCHAR</td>
</tr>

<tr>
<td>copies_available</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>borrows</code> Table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td>borrow_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>user_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>book_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>borrowed_at</td>
<td>DATETIME</td>
</tr>

<tr>
<td>returned_at</td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
Output

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td>book_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>avg_borrow_duration_days</td>
<td>DECIMAL</td>
</tr>

<tr>
<td>has_over_10_copies</td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>

<h3>Example</h3>

Input

<code>books</code> Table

<table>
<thead>
<tr>
<th>book_id</th>
<th>title</th>
<th>copies_available</th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>Dune</td>
<td>12</td>
</tr>

<tr>
<td>2</td>
<td>Sapiens</td>
<td>8</td>
</tr>

<tr>
<td>3</td>
<td>Clean Code</td>
<td>15</td>
</tr>
</tbody>
</table>
<code>borrows</code> Table

<table>
<thead>
<tr>
<th>borrow_id</th>
<th>user_id</th>
<th>book_id</th>
<th>borrowed_at</th>
<th>returned_at</th>
</tr>
</thead>

<tbody>
<tr>
<td>101</td>
<td>10</td>
<td>1</td>
<td>2026-01-01 09:00:00</td>
<td>2026-01-06 09:00:00</td>
</tr>

<tr>
<td>102</td>
<td>11</td>
<td>1</td>
<td>2026-01-10 10:00:00</td>
<td>2026-01-13 22:00:00</td>
</tr>

<tr>
<td>103</td>
<td>12</td>
<td>2</td>
<td>2026-01-02 12:00:00</td>
<td>2026-01-04 12:00:00</td>
</tr>

<tr>
<td>104</td>
<td>13</td>
<td>2</td>
<td>2026-01-05 09:00:00</td>
<td>NULL</td>
</tr>

<tr>
<td>105</td>
<td>14</td>
<td>3</td>
<td>2026-01-03 08:00:00</td>
<td>2026-01-10 08:00:00</td>
</tr>
</tbody>
</table>
Output

<table>
<thead>
<tr>
<th>book_id</th>
<th>avg_borrow_duration_days</th>
<th>has_over_10_copies</th>
</tr>
</thead>

<tbody>
<tr>
<td>3</td>
<td>7.00</td>
<td>Yes</td>
</tr>

<tr>
<td>1</td>
<td>4.25</td>
<td>Yes</td>
</tr>

<tr>
<td>2</td>
<td>2.00</td>
<td>No</td>
</tr>
</tbody>
</table>
Explanation

For book 1, there are two completed borrows. The durations are 5.00 days (Jan 1 → Jan 6) and 3.50 days (Jan 10 10:00 → Jan 13 22:00). The average borrowing duration is (5.00 + 3.50) / 2 = 4.25 days. Since <code>copies_available = 12</code>, the book is flagged as <code>&#39;Yes&#39;</code>.

For book 2, only one borrow is completed (the other has <code>returned_at = NULL</code> and is excluded). The completed duration is 2.00 days. Since <code>copies_available = 8</code>, it is flagged as <code>&#39;No&#39;</code>.

For book 3, there is one completed borrow lasting 7.00 days, and <code>copies_available = 15</code>, so it is flagged as <code>&#39;Yes&#39;</code>.

Write a SQL query to compute the average borrowing duration and identify books with over 10 copies.

Digital Library Borrowing Metrics

Let’s say that you’re a data scientist working on a distribution team at Amazon.

Create a report displaying which shipments were delivered to customers during their membership period.

If the transaction is shipped during the membership period, column <code>is_member</code> should have the value <code>Y</code>. If not, the column should have the value <code>N</code>.

Hint: You may assume that <code>customer_id</code> is unique and that shipments are made only to registered customers.

Example:

Input:

<code>customers</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>customer_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>membership_start_date</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>membership_end_date</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
<code>shipments</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>shipment_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>ship_date</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>customer_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>quantity</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>shipment_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>ship_date</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>customer_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>is_member</code></td>
<td>TEXT</td>
</tr>

<tr>
<td><code>quantity</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Create a report displaying which shipments were delivered to customers during their membership period.

Completed Shipments

Given two strings, <code>string1</code> and <code>string2</code>, write a function <code>str_map</code> to determine if there exists a one-to-one correspondence (bijection) between the characters of <code>string1</code> and <code>string2</code>.

For the two strings, our correspondence must be between characters in the same position/index.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>string1 = &#39;qwe&#39;
string2 = &#39;asd&#39;

string_map(string1, string2) == True

# q = a, w = s, and e = d
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>string1 = &#39;donut&#39;
string2 = &#39;fatty&#39;

string_map(string1, string2) == False
# cannot map two distinct characters to two equal characters
</code></pre>

Example 3:

Input:

<pre tabindex="0" class="chroma"><code>string1 = &#39;enemy&#39;
string2 = &#39;enemy&#39;

string_map(string1, string2) == True
# there exists a one-to-one correspondence between equivalent strings
</code></pre>

Example 4:

Input:

<pre tabindex="0" class="chroma"><code>string1 = &#39;enemy&#39;
string2 = &#39;ymene&#39;

string_map(string1, string2) == False
# since our correspondence must be between characters of the same index, this case returns &#39;False&#39; as we must map e = y AND e = e
</code></pre>

String Mapping

There was a robbery from the ATM at the bank where you work. Some unauthorized withdrawals were made, and you need to help your bank find out more about those withdrawals.

However, the only information you have is that there was more than 1 withdrawal, they were all performed in 10-second gaps, and no legitimate transactions were performed in between two fraudulent withdrawals.

We’re given a table of bank transactions with three columns, <code>user_id</code>, a deposit or withdrawal value <code>transaction_value</code>, and <code>created_at</code> time for each transaction.

Write a query to retrieve all user IDs in ascending order whose transactions have exactly a 10-second gap from one another.

Note: Assume that there are only withdrawals from the ATM, which are denoted with a positive <code>transaction_value</code>

Example: 

Input:

<code>bank_transactions</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>transaction_value</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>
For given table <code>bank_transactions</code>:

<table>
<thead>
<tr>
<th><code>user_id</code></th>
<th><code>created_at</code></th>
<th><code>transaction_value</code></th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>2017-01-01 10:10:15</td>
<td>10</td>
</tr>

<tr>
<td>2</td>
<td>2017-01-01 11:11:11</td>
<td>20</td>
</tr>

<tr>
<td>3</td>
<td>2017-01-01 12:12:12</td>
<td>10</td>
</tr>

<tr>
<td>4</td>
<td>2017-01-01 10:10:20</td>
<td>30</td>
</tr>

<tr>
<td>5</td>
<td>2017-01-01 10:10:34</td>
<td>40</td>
</tr>

<tr>
<td>6</td>
<td>2017-01-01 11:11:21</td>
<td>50</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th><code>user_id</code></th>
</tr>
</thead>

<tbody>
<tr>
<td>2</td>
</tr>

<tr>
<td>6</td>
</tr>
</tbody>
</table>

There was a robbery from the ATM at the bank where you work. Some unauthorized withdrawals were made, and you need to help your bank find out more about those withdrawals.

ATM Robbery

Let’s say that you’re a data scientist at Robinhood. 

How do we measure the launch of Robinhood’s fractional shares program?

Let’s say you are a data scientist at Robinhood.

Robinhood is introducing a program to allow users to buy fractional shares of publically listed companies.

Focusing in on the activity of new users, which of the following metrics would be the LEAST important to keep track of in determining if the program added value to Robinhood’s platform for new users?

Let's say you are a data scientist at Robinhood. 



Robinhood is introducing a program to allow users to buy fractional shares of publically listed companies.



Focusing in on the activity of new users, which of the following metrics would be the LEAST important to keep track of in determining if the program added value to Robinhood's platform for new users?

Calculate Moving Average	SQL	Easy
Predict Customer Churn	Machine Learning	Medium
A/B Test Significance	Statistics	Medium
Optimize Query Performance	SQL	Hard
Feature Importance Analysis	Machine Learning	Medium
Clean Missing Data	Python	Easy
Neural Network Architecture	Deep Learning	Hard
Calculate Cohort Retention	SQL	Medium
Bayesian Probability	Statistics	Easy
Recommend Similar Products	Machine Learning	Hard

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