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Pinterest Interview Questions

<p>Pinterest is a social media company that enables discovery of things like recipes, style inspiration, home hacks and more</p>

Pinterest is a social media company that enables discovery of things like recipes, style inspiration, home hacks and more

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A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

Pinterest Interview Guides

<p>You’re given a table that represents search results from searches on Facebook. The <code>query</code> column is the search term, the <code>position</code> column represents each position the search result came in, and the <code>rating</code> column represents the human rating of the search result from 1 to 5 where 5 is high relevance and 1 is low relevance.</p>

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

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

<p><code>search_results</code> table</p>

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

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

<tr>
<td><code>result_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>position</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>rating</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<p>You want to be able to compute a metric that measures the precision of the ranking system based on position. For example, if the results for dog and cat are…</p>

<table>
<thead>
<tr>
<th>query</th>
<th>result_id</th>
<th>position</th>
<th>rating</th>
<th>notes</th>
</tr>
</thead>

<tbody>
<tr>
<td>dog</td>
<td>1000</td>
<td>1</td>
<td>2</td>
<td>picture of hotdog</td>
</tr>

<tr>
<td>dog</td>
<td>998</td>
<td>2</td>
<td>4</td>
<td>dog walking</td>
</tr>

<tr>
<td>dog</td>
<td>342</td>
<td>3</td>
<td>1</td>
<td>zebra</td>
</tr>

<tr>
<td>cat</td>
<td>123</td>
<td>1</td>
<td>4</td>
<td>picture of cat</td>
</tr>

<tr>
<td>cat</td>
<td>435</td>
<td>2</td>
<td>2</td>
<td>cat memes</td>
</tr>

<tr>
<td>cat</td>
<td>545</td>
<td>3</td>
<td>1</td>
<td>pizza shops</td>
</tr>
</tbody>
</table>
<p>…we would rank ‘cat’ as having a better search result ranking precision than ‘dog’ based on the correct sorting by rating.</p>

<p>Write a query to create a metric that can validate and rank the queries by their search result precision. Round the metric (avg_rating column) to 2 decimal places.</p>

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

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

<tbody>
<tr>
<td>query</td>
<td>VARCHAR</td>
</tr>

<tr>
<td>avg_rating</td>
<td>FLOAT</td>
</tr>
</tbody>
</table>


<p>Let’s say you want to create a metric that is proportional to field A and inversely proportional to field B. Which of the following metrics would fit these criteria?</p>


Let's say you want to create a metric that is proportional to field A and inversely proportional to field B. Which of the following metrics would fit these criteria?

Weighted Average Metric

Write a query to create a metric that can validate and rank the queries by their search result precision.

Search Ratings

<p>Given a table of product subscriptions with a subscription start date and end date for each user, write a query that returns true or false whether or not each user has a subscription date range that overlaps with any other completed subscription.</p>

<p>Completed subscriptions have <code>end_date</code> recorded.</p>

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

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

<p><code>subscriptions</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>start_date</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>end_date</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>

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

<tbody>
<tr>
<td>1</td>
<td>2019-01-01</td>
<td>2019-01-31</td>
</tr>

<tr>
<td>2</td>
<td>2019-01-15</td>
<td>2019-01-17</td>
</tr>

<tr>
<td>3</td>
<td>2019-01-29</td>
<td>2019-02-04</td>
</tr>

<tr>
<td>4</td>
<td>2019-02-05</td>
<td>2019-02-10</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

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

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

<tr>
<td>2</td>
<td>1</td>
</tr>

<tr>
<td>3</td>
<td>1</td>
</tr>

<tr>
<td>4</td>
<td>0</td>
</tr>
</tbody>
</table>


Subscription Overlap

<p>Let’s say you work at Pinterest. On Pinterest’s internal database, the table <code>pins</code> contains an identifier number and creation date/time of pins (content such as pictures or videos) that a user posted on his profile.</p>

<p>The table <code>event_log</code> is a log table containing data about all actions on pins.</p>

<p>Possible action types are:</p>

<ul>
<li><code>&#34;View&#34;</code> - Logged when pins appear on a user’s screen.</li>
<li><code>&#34;Engagement&#34;</code> - Logged when actions such as saves or pin-clicks occur.</li>
</ul>

<p>Write a query to determine the percentage of users that have viewed at least one content within seven days from the content being posted and with at least one engagement recorded on any pin, regardless of when it occurred.</p>

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

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

<p><code>pins</code> table</p>

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

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

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
<p><code>event_log</code> table</p>

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

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

<tr>
<td><code>pin_id</code></td>
<td>INTEGER</td>
</tr>

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

<tr>
<td><code>action_type</code></td>
<td>VARCHAR</td>
</tr>

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

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

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


Pinterest Interview Questions

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