Prepare for and practice interview questions from Under Armour across topics like Algorithms, Analytics, Takehome and more.

Under Armour Interview Questions

Under Armour Interview Guides

Select the 2nd highest salary in the engineering department

2nd Highest Salary

Write a query to identify customers who placed more than three transactions each in both 2019 and 2020

Customer Orders

Write a query to get the average order value by gender rounded to two decimal places

Average Order Value

Write a query to show the number of users, transactions, and total order amount per month in 2020

Monthly Customer Report

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

Machine Learning

Interpret coefficients of logistic regression for categorical and boolean variables

Coefficients of Logistic Regression

Which model would perform better and why?

Booking Regression

Lasso vs Ridge

In which case would you use a bagging algorithm versus a boosting algorithm

Bagging vs Boosting

What are the logistic and softmax functions? What is the difference between the two?

Softmax vs Logistic

Behavioral

Describing a data project and its challenges

Hurdles In Data Projects

Strategically resolving misaligned expectations with stakeholders for a successful project outcome

Stakeholder Communication

How to present complex data insights with clarity and adaptability tailored to a specific audience

Presentations and Insights

How would you answer when an Interviewer asks why you applied to their company?

Why Do You Want to Work With Us

What do you tell an interviewer when they ask you what your strengths and weaknesses are?

Your Strengths and Weaknesses

Product Sense & Metrics

How would you investigate the drop in Facebook composer posts per user, especially photo posts

Post Composer Drop

Unified Inbox

What are the top five metrics you would start tracking to understand the health of Google Docs

Docs Metrics

Pitching a feature idea that could drive success for Instagram Stories

Boosting Instagram Stories

The role of A/B testing in measuring the success rate of an analytics experiment

Success Measurement

Business Case

Why would the number of applicants be steadily decreasing while job postings remain the same

Declining Applicants

Friend Requests Down

How would you decide whether Google should build a game feature for Google Home

Game Feature Home

What would be your recommendation on utilizing a customer success manager versus just a free trial to get new or existing customers to use the new product

Customer Success vs. Free Trial

How would you investigate a 10% drop in usage on Google Docs

Google Docs Drop

<p>Write a SQL query to select the 2nd highest salary in the engineering department.</p>

<p><strong>Note:</strong> If more than one person shares the highest salary, the query should select the next highest salary.</p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>employees</code> table</p>

<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>
<p><code>departments</code> table</p>

<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>
<p><strong>Output:</strong></p>

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

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


<p>Write a query to identify customers who placed more than three transactions each in both 2019 and 2020.</p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>transactions</code> table</p>

<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>
<p><code>users</code> table</p>

<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>
<p> 
<strong>Output:</strong></p>

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

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


<p>Which of the following queries will return a list of customers and the total amount they have spent on orders?</p>


Which of the following queries will return a list of customers and the total amount they have spent on orders?

<p>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).</p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>transactions</code> table</p>

<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>
<p><code>products</code> table</p>

<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>
<p><code>users</code> table</p>

<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>
<p><strong>Output:</strong></p>

<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>


<p>Let’s say we have a table with an <code>id</code> and <code>name</code> fields. The table holds over 100 million rows and we want to sample a random row in the table without throttling the database.</p>

<p>Write a query to randomly sample a row from this table.</p>

<p><strong>Input:</strong></p>

<p><code>big_table</code> table</p>

<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>
</tbody>
</table>


Write a query to randomly sample a row from a big table.

Random SQL Sample

<p>A team wants to A/B test multiple different changes through a sign-up funnel.</p>

<p>For example, on a page, a button is currently red and at the top of the page. They want to see if changing a button from red to blue and/or from the top of the page to the bottom of the page will increase click-through.</p>

<p>How would you set up this test?</p>


<p>Your team wants to run an AB test on the color (red or blue) and position (top/bottom of the page) of a button that links to a promotion.</p>

<p>How many different variants of the test should you run to see the effect that a red button has on the bottom of the page, if currently the button is blue and on the top of the page.</p>


Your team wants to run an AB test on the color (red or blue) and position (top/bottom of the page) of a button that links to a promotion.

How many different variants of the test should you run to see the effect that a red button has on the bottom of the page, if currently the button is blue and on the top of the page.

A/B Test Variants

Button AB Test

A/B Testing

<p>Given three tables, representing customer transactions and customer attributes:</p>

<p>Write a query to get the average order value by gender.</p>

<p><em>Note: We’re looking at the average order value by users that have ever placed an order. Additionally, please round your answer to two decimal places.</em></p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>transactions</code> table</p>

<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>
<p><code>users</code> table</p>

<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>
<p><code>products</code> table</p>

<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>
<p><strong>Output:</strong></p>

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

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

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


<p>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.</p>

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

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>users</code> table</p>

<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>
<p><code>purchases</code> table</p>

<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>
<p><strong>Output:</strong></p>

<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

<p>As an accountant for a local grocery store, you have been tasked with calculating the daily sales of each product since their last restocking.</p>

<p>You have been provided with three tables: <code>products</code>, <code>sales</code>, and <code>restocking</code>. The <code>products</code> table contains information about each product, the <code>sales</code> table records the sales transactions, and the <code>restocking</code> table tracks the restocking events.</p>

<p>Write a query to retrieve the running total of sales for each product since its last restocking event.</p>

<p><strong><em>Notes:</em></strong> <em>The <code>sales_since_last_restock</code> column represents the cumulative sales of the product for each day since its last restocking event. Order the result set by <code>product_id</code>.</em></p>

<p>Example:</p>

<p><strong>Input:</strong></p>

<p>Table <code>products</code>:</p>

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

<tbody>
<tr>
<td>product_id</td>
<td>int</td>
</tr>

<tr>
<td>product_name</td>
<td>varchar</td>
</tr>
</tbody>
</table>
<p>Table <code>sales</code>:</p>

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

<tbody>
<tr>
<td>sales_id</td>
<td>int</td>
</tr>

<tr>
<td>product_id</td>
<td>int</td>
</tr>

<tr>
<td>date</td>
<td>date</td>
</tr>

<tr>
<td>sold_count</td>
<td>int</td>
</tr>
</tbody>
</table>
<p>Table <code>restocking</code>:</p>

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

<tbody>
<tr>
<td>restock_id</td>
<td>int</td>
</tr>

<tr>
<td>product_id</td>
<td>int</td>
</tr>

<tr>
<td>restock_date</td>
<td>date</td>
</tr>
</tbody>
</table>
<p><strong>Output</strong></p>

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

<tbody>
<tr>
<td>product_name</td>
<td>varchar</td>
</tr>

<tr>
<td>date</td>
<td>date</td>
</tr>

<tr>
<td>sales_since_last_restock</td>
<td>int</td>
</tr>
</tbody>
</table>


Calculate daily sales of each product since last restocking.

Cumulative Sales Since Last Restocking

<p>Let’s say we’re comparing two machine learning algorithms. In which case would you use a bagging algorithm versus a boosting algorithm? </p>

<p>Give an example of the tradeoffs between the two.</p>


<p>In machine learning, when would you use a bagging algorithm over a boosting algorithm?</p>


In machine learning, when would you use a bagging algorithm over a boosting algorithm?

Bagging vs. Boosting

<p>Let’s say we want to build a new delivery time estimate model for consumers ordering food delivery.</p>

<p>How would you determine if the new model predicts delivery times better than the old model?</p>


<p>When rolling out a new delivery time estimate model in production, what is an important consideration?</p>

When rolling out a new delivery time estimate model in production, what is an important consideration?

Delivery Estimate Model I

<p>What is one way to measure the performance of a new delivery time estimate model for food delivery?</p>

What is one way to measure the performance of a new delivery time estimate model for food delivery?

Delivery Estimate Model II

How would you determine if the new model predicts delivery times better than the old model

Delivery Estimate Model

<p>Given a sorted list of positive integers with some entries being <code>None</code>, write a function to return a new list where all <code>None</code> values are replaced with the most recent non-<code>None</code> value in the list.</p>

<p><em>Note: If the first entry in the list is <code>None</code>, assume the previous entry was <code>0</code>.</em></p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="n">input_list</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="kc">None</span><span class="p">,</span><span class="kc">None</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="kc">None</span><span class="p">]</span>
</span></span></code></pre>

<p><strong>Output:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="k">def</span> <span class="nf">fill_none</span><span class="p">(</span><span class="n">input_list</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">5</span><span class="p">]</span> 
</span></span></code></pre>


Write a function to return a new list where all empty values are replaced with the most recent non-empty value in the list.

Fill None Values

Data Structures & Algorithms

<p>Let’s say we want to build a model to predict booking prices on Airbnb.</p>

<p>Between linear regression and random forest regression, which model would perform better and why?</p>


<p>What are the two key concepts of random forest regression?</p>

What are the two key concepts of random forest regression?

<p>Tell me about a data project that didn’t go the way you expected. What did you set out to do, what surprised you, and how did you handle it?</p>


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


<p>What does a p-value in a statistical test represent?</p>

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

P-value to a Layman I

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

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

Explain what a p-value is to someone who is not technical

P-value to a Layman

Statistics

<p>Let’s say that on Facebook composer, the posting tool, drops from 3% posts per user last month to 2.5% post per user today. </p>

<p>How would you investigate what happened?</p>

<p>Let’s say the drop is in photo posts. What would you investigate now?</p>


<p>In the analysis of a drop in photo posts per user on a social media site like Facebook, which factor(s) could influence the change in the average number of posts per user?</p>


In the analysis of a drop in photo posts per user on a social media site like Facebook, which factor(s) could influence the change in the average number of posts per user?

<p>You’re a data analyst working for Burlington studying customer behavior during the annual Black Friday shopping spree. Each customer may visit the store multiple times throughout the day and make several purchases across different product categories. The marketing team wants to understand which customer segments were most engaged.</p>

<p>Write a SQL query to compute the following metrics for each product category:</p>

<ol>
<li>Total number of unique customers who purchased from that category</li>
<li>Average spend per customer (rounded to 2 decimal places)</li>
<li>Percentage of customers who made more than one purchase in that category (rounded to 2 decimal places)</li>
</ol>

<p>Sort the final results in descending order by average spend per customer.</p>

<p><strong><em>Notes:</em></strong></p>

<ul>
<li><em>A “purchase” means a single row in the purchases table.</em></li>
<li><em>A customer who buys multiple items in one visit still counts as multiple purchases.</em></li>
<li><em>If a customer purchased from a category only once, they should not count toward the “multiple purchase” percentage.</em></li>
<li><em>Every category present in the purchases table should appear in the output.</em></li>
</ul>

<p><strong>Schema</strong></p>

<p><strong>Input</strong></p>

<p><strong><code>purchases</code> table</strong></p>

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

<tbody>
<tr>
<td>purchase_id</td>
<td>INTEGER</td>
</tr>

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

<tr>
<td>category</td>
<td>VARCHAR</td>
</tr>

<tr>
<td>amount</td>
<td>DECIMAL</td>
</tr>

<tr>
<td>purchase_time</td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
<p><strong>Output</strong></p>

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

<tbody>
<tr>
<td>category</td>
<td>VARCHAR</td>
</tr>

<tr>
<td>unique_customers</td>
<td>INTEGER</td>
</tr>

<tr>
<td>avg_spend_per_customer</td>
<td>DECIMAL</td>
</tr>

<tr>
<td>pct_multi_purchase_customers</td>
<td>DECIMAL</td>
</tr>
</tbody>
</table>
<p><strong>Example</strong></p>

<p><strong>Input</strong></p>

<p><strong><code>purchases</code> table</strong></p>

<table>
<thead>
<tr>
<th>purchase_id</th>
<th>customer_id</th>
<th>category</th>
<th>amount</th>
<th>purchase_time</th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>101</td>
<td>Electronics</td>
<td>120</td>
<td>2025-11-28 09:10:00</td>
</tr>

<tr>
<td>2</td>
<td>101</td>
<td>Electronics</td>
<td>80</td>
<td>2025-11-28 10:00:00</td>
</tr>

<tr>
<td>3</td>
<td>102</td>
<td>Clothing</td>
<td>40</td>
<td>2025-11-28 11:15:00</td>
</tr>

<tr>
<td>4</td>
<td>103</td>
<td>Electronics</td>
<td>300</td>
<td>2025-11-28 13:30:00</td>
</tr>

<tr>
<td>5</td>
<td>102</td>
<td>Electronics</td>
<td>150</td>
<td>2025-11-28 14:10:00</td>
</tr>

<tr>
<td>6</td>
<td>102</td>
<td>Clothing</td>
<td>10</td>
<td>2025-11-28 16:20:00</td>
</tr>

<tr>
<td>7</td>
<td>103</td>
<td>Clothing</td>
<td>50</td>
<td>2025-11-28 17:20:00</td>
</tr>
</tbody>
</table>
<p><strong>Output</strong></p>

<table>
<thead>
<tr>
<th>category</th>
<th>unique_customers</th>
<th>avg_spend_per_customer</th>
<th>pct_multi_purchase_customers</th>
</tr>
</thead>

<tbody>
<tr>
<td>Electronics</td>
<td>3</td>
<td>216.67</td>
<td>33.33</td>
</tr>

<tr>
<td>Clothing</td>
<td>2</td>
<td>50.00</td>
<td>50.00</td>
</tr>
</tbody>
</table>
<p><strong>Explanation</strong></p>

<p>For Electronics, there are three unique customers: 101, 102, and 103. Their spend amounts are 200 for customer 101 (120 + 80), 150 for customer 102, and 300 for customer 103, giving an average spend of 216.67. Only customer 101 made more than one purchase, so the multi-purchase rate is 33.33%.</p>

<p>For Clothing, there are two unique customers: 102 and 103. Customer 102 spent a total of 50 (40 + 10), while customer 103 spent 50, resulting in an average of 50.00. Customer 102 is the only one with multiple purchases, leading to a multi-purchase rate of 50.00%.</p>


Write a SQL query to compute metrics for each product category.

Black Friday Shopping Spree

<p>Given the <code>transactions</code> table, write a query to get the max quantity purchased for each distinct <code>product_id</code>, every year. </p>

<p>The output should include the <code>year</code>, <code>product_id</code>, and <code>max_quantity</code> for that product sorted by year and <code>product_id</code> ascending.</p>

<h3>Schema:</h3>

<p><strong>Input:</strong></p>

<p><code>transactions</code> table</p>

<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>
<p><strong>Output:</strong></p>

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

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

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

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

<h3>Example</h3>

<p><strong>Input:</strong></p>

<table>
<thead>
<tr>
<th>id</th>
<th>user_id</th>
<th>created_at</th>
<th>product_id</th>
<th>quantity</th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>59</td>
<td>2019-10-05 00:00:00</td>
<td>500</td>
<td>1</td>
</tr>

<tr>
<td>2</td>
<td>84</td>
<td>2019-08-11 00:00:00</td>
<td>500</td>
<td>2</td>
</tr>

<tr>
<td>3</td>
<td>21</td>
<td>2020-01-25 00:00:00</td>
<td>500</td>
<td>3</td>
</tr>

<tr>
<td>4</td>
<td>47</td>
<td>2019-12-25 00:00:00</td>
<td>500</td>
<td>2</td>
</tr>

<tr>
<td>5</td>
<td>100</td>
<td>2020-03-05 00:00:00</td>
<td>500</td>
<td>2</td>
</tr>

<tr>
<td>6</td>
<td>45</td>
<td>2019-06-30 00:00:00</td>
<td>500</td>
<td>1</td>
</tr>

<tr>
<td>7</td>
<td>44</td>
<td>2020-07-07 00:00:00</td>
<td>500</td>
<td>1</td>
</tr>

<tr>
<td>8</td>
<td>38</td>
<td>2020-09-23 00:00:00</td>
<td>500</td>
<td>2</td>
</tr>

<tr>
<td>9</td>
<td>45</td>
<td>2020-03-08 00:00:00</td>
<td>500</td>
<td>2</td>
</tr>

<tr>
<td>10</td>
<td>16</td>
<td>2020-04-22 00:00:00</td>
<td>999</td>
<td>1</td>
</tr>

<tr>
<td>11</td>
<td>17</td>
<td>2020-06-06 00:00:00</td>
<td>999</td>
<td>2</td>
</tr>

<tr>
<td>12</td>
<td>41</td>
<td>2020-09-17 00:00:00</td>
<td>999</td>
<td>1</td>
</tr>

<tr>
<td>13</td>
<td>34</td>
<td>2019-07-05 00:00:00</td>
<td>999</td>
<td>1</td>
</tr>

<tr>
<td>14</td>
<td>78</td>
<td>2020-02-16 00:00:00</td>
<td>999</td>
<td>3</td>
</tr>

<tr>
<td>15</td>
<td>16</td>
<td>2020-05-22 00:00:00</td>
<td>999</td>
<td>4</td>
</tr>

<tr>
<td>16</td>
<td>4</td>
<td>2020-05-10 00:00:00</td>
<td>999</td>
<td>2</td>
</tr>

<tr>
<td>17</td>
<td>25</td>
<td>2019-12-15 00:00:00</td>
<td>999</td>
<td>1</td>
</tr>

<tr>
<td>18</td>
<td>71</td>
<td>2020-05-03 00:00:00</td>
<td>999</td>
<td>1</td>
</tr>

<tr>
<td>19</td>
<td>3</td>
<td>2020-08-03 00:00:00</td>
<td>999</td>
<td>2</td>
</tr>

<tr>
<td>20</td>
<td>19</td>
<td>2019-03-13 00:00:00</td>
<td>999</td>
<td>5</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th>year</th>
<th>product_id</th>
<th>max_quantity</th>
</tr>
</thead>

<tbody>
<tr>
<td>2019</td>
<td>500</td>
<td>2</td>
</tr>

<tr>
<td>2019</td>
<td>999</td>
<td>5</td>
</tr>

<tr>
<td>2020</td>
<td>500</td>
<td>3</td>
</tr>

<tr>
<td>2020</td>
<td>999</td>
<td>4</td>
</tr>
</tbody>
</table>


Max Quantity

<p>Write a query to get the cost of all transactions by user ordered by total cost descending.</p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>transactions</code> table</p>

<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>
<p><code>products</code> table</p>

<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>
<p><code>users</code> table</p>

<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>created_at</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

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

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

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

<tr>
<td><code>total_cost</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>
<p><em>Note: Round the total cost to 2 decimal places.</em></p>


Write a query to get the cost of all transactions by user ordered by total cost descending

Total Transactions

<p>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.</p>

<p>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.</p>

<p>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.</p>

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

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

<p><strong>Example:</strong> </p>

<p><strong>Input:</strong></p>

<p><code>bank_transactions</code> table</p>

<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>
<p>For given table <code>bank_transactions</code>:</p>

<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>
<p><strong>Output:</strong></p>

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

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

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


<p>Let’s say that you’re looking at the metrics of a job board. You see that the number of job postings per day has more or less remained the same the last few months but the number of applicants that have applied to jobs has steadily been decreasing.</p>

<p>Why would this be happening?</p>


<p>What is the difference between covariance and correlation? Provide an example.</p>


Explain the difference between covariance and correlation and provide an example

Covariance vs Correlation

<p>How does random forest generate the forest? Additionally, why would we use it over other algorithms such as logistic regression?</p>


<p>What happens when you average the output on multiple decision trees?</p>


What happens when you average the output on multiple decision trees?

Average Trees

How does random forest generate the forest and why use it over logistic regression

Random Forest Explanation

<p>What are the assumptions of linear regression?</p>


Which assumption of the residuals of the standard linear regression model can not be overcome by increasing the sample size?

Regression assumptions

What are the assumptions of linear regression?

Assumptions of Linear Regression

<p>Let’s say you’re given all the different marketing channels along with their respective marketing costs at a company called Mode, that sells B2B analytics dashboards.</p>

<p>What metrics would you use to determine the value of each marketing channel?</p>


<p>When determining the value of each marketing channel for the company Mode, which metric is considered the key metric?</p>

When determining the value of each marketing channel for the company Mode, which metric is considered the key metric?

Marketing Channel Metrics

What metrics would you use to determine the value of each marketing channel?

Analytics

<p>Given two strings, write a function to return <code>True</code> if the strings are anagrams of each other and <code>False</code> if they are not.</p>

<p><em>Note: A word is not an anagram of itself.</em></p>

<p><strong>Example 1:</strong></p>

<p><strong>Input:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="n">string_1</span> <span class="o">=</span> <span class="s2">&#34;listen&#34;</span>
</span></span><span class="line"><span class="cl"><span class="n">string_2</span> <span class="o">=</span> <span class="s2">&#34;silent&#34;</span>
</span></span></code></pre>

<p><strong>Output:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="kc">True</span>
</span></span></code></pre>

<p><strong>Example 2:</strong></p>

<p><strong>Input:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="n">string_1</span> <span class="o">=</span> <span class="s2">&#34;banana&#34;</span>
</span></span><span class="line"><span class="cl"><span class="n">string_2</span> <span class="o">=</span> <span class="s2">&#34;bandana&#34;</span>
</span></span></code></pre>

<p><strong>Output:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="kc">False</span>
</span></span></code></pre>


Write a function to return True if two strings are anagrams of each other and False if they are not

Valid Anagram

<p>Let’s say you’re a data scientist at LinkedIn where you’re working on a product that sends qualified job candidates to companies. The team has launched a new feature that allows candidates to message hiring managers at companies directly during the interview process to get updates on their status.</p>

<p>Due to engineering constraints, the company can’t AB test the feature before launching it.</p>

<p>How would you analyze how the feature is performing?</p>


How would you analyze the performance of a new LinkedIn feature that lets candidates message hiring managers during the interview process

Recruiting Leads

<p>You’re a data scientist at YouTube. Leadership wants to revisit how the platform measures success, not for a specific new feature, but for the product as a whole given its current state.</p>

<p>How would you define and measure success for YouTube? Identify your primary and secondary metrics, explain your rationale for each, and discuss how you would choose the right thresholds for any engagement-based metrics you propose.</p>


<p>What’s the difference between Lasso and Ridge Regression?</p>


<p>Under what circumstances is it recommended to use Lasso regression over Ridge regression?</p>

Under what circumstances is it recommended to use Lasso regression over Ridge regression?

<p>Given a table containing data for monthly sales, write a query to find the total amount of each product sold for each month with each product as its own column in the output table.</p>

<h3>Schema</h3>

<p><strong>Input:</strong></p>

<p><code>monthly_sales</code> table</p>

<table>
<thead>
<tr>
<th><code>month</code></th>
<th><code>product_id</code></th>
<th><code>amount_sold</code></th>
</tr>
</thead>

<tbody>
<tr>
<td>2021-01-01</td>
<td>1</td>
<td>100</td>
</tr>

<tr>
<td>2021-01-01</td>
<td>2</td>
<td>300</td>
</tr>

<tr>
<td>2021-02-01</td>
<td>3</td>
<td>200</td>
</tr>

<tr>
<td>2021-03-01</td>
<td>4</td>
<td>250</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th><strong>month</strong></th>
<th><strong>1</strong></th>
<th><strong>2</strong></th>
<th><strong>3</strong></th>
<th><strong>4</strong></th>
</tr>
</thead>

<tbody>
<tr>
<td>2021-01-01</td>
<td>100</td>
<td>0</td>
<td>300</td>
<td>0</td>
</tr>

<tr>
<td>2021-02-01</td>
<td>0</td>
<td>200</td>
<td>0</td>
<td>0</td>
</tr>

<tr>
<td>2021-03-01</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>250</td>
</tr>
</tbody>
</table>

<h3>Example</h3>

<p><strong>Input:</strong></p>

<p><strong><code>monthly_sales</code> table</strong></p>

<table>
<thead>
<tr>
<th>month</th>
<th>product_id</th>
<th>amount_sold</th>
</tr>
</thead>

<tbody>
<tr>
<td>2021-01-01</td>
<td>1</td>
<td>100</td>
</tr>

<tr>
<td>2021-01-01</td>
<td>2</td>
<td>0</td>
</tr>

<tr>
<td>2021-01-01</td>
<td>3</td>
<td>250</td>
</tr>

<tr>
<td>2021-01-01</td>
<td>4</td>
<td>300</td>
</tr>

<tr>
<td>2021-02-01</td>
<td>1</td>
<td>50</td>
</tr>

<tr>
<td>2021-02-01</td>
<td>2</td>
<td>200</td>
</tr>

<tr>
<td>2021-02-01</td>
<td>3</td>
<td>0</td>
</tr>

<tr>
<td>2021-02-01</td>
<td>4</td>
<td>300</td>
</tr>

<tr>
<td>2021-03-01</td>
<td>1</td>
<td>400</td>
</tr>

<tr>
<td>2021-03-01</td>
<td>2</td>
<td>150</td>
</tr>

<tr>
<td>2021-03-01</td>
<td>3</td>
<td>200</td>
</tr>

<tr>
<td>2021-03-01</td>
<td>4</td>
<td>300</td>
</tr>

<tr>
<td>2021-04-01</td>
<td>1</td>
<td>150</td>
</tr>

<tr>
<td>2021-04-01</td>
<td>2</td>
<td>200</td>
</tr>

<tr>
<td>2021-04-01</td>
<td>3</td>
<td>50</td>
</tr>

<tr>
<td>2021-04-01</td>
<td>4</td>
<td>300</td>
</tr>

<tr>
<td>2021-05-01</td>
<td>1</td>
<td>100</td>
</tr>

<tr>
<td>2021-05-01</td>
<td>2</td>
<td>150</td>
</tr>

<tr>
<td>2021-05-01</td>
<td>3</td>
<td>0</td>
</tr>

<tr>
<td>2021-05-01</td>
<td>4</td>
<td>300</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th>month</th>
<th>1</th>
<th>2</th>
<th>3</th>
<th>4</th>
</tr>
</thead>

<tbody>
<tr>
<td>2021-01-01</td>
<td>100</td>
<td>0</td>
<td>250</td>
<td>300</td>
</tr>

<tr>
<td>2021-02-01</td>
<td>50</td>
<td>200</td>
<td>0</td>
<td>300</td>
</tr>

<tr>
<td>2021-03-01</td>
<td>400</td>
<td>150</td>
<td>200</td>
<td>300</td>
</tr>

<tr>
<td>2021-04-01</td>
<td>150</td>
<td>200</td>
<td>50</td>
<td>300</td>
</tr>

<tr>
<td>2021-05-01</td>
<td>100</td>
<td>150</td>
<td>0</td>
<td>300</td>
</tr>
</tbody>
</table>


Monthly Product Sales

<p>How would you interpret coefficients of logistic regression for categorical and boolean variables?</p>


<p>Why is one-hot encoding recommended for categorical variables in logistic regression models?</p>

Why is one-hot encoding recommended for categorical variables in logistic regression models?

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