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Twitter Interview Questions

<p>Twitter is an online news and social networking service on which users post and interact with limited length messages known as tweets</p>

Twitter is an online news and social networking service on which users post and interact with limited length messages known as tweets

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A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

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<p>Twitter wants to roll out more push notifications to users because they think users are missing out on good content. Twitter decides to do this in an A/B test. </p>

<p>Let’s say that after we release more notifications, we suddenly see the total number of unsubscribes increase.</p>

<p>We’re given two tables, <code>events</code> where actions are <code>login</code>, <code>nologin</code>, and <code>unsubscribe</code> and another table called <code>variants</code> where user’s are bucketed into a <code>control</code> and a <code>variant</code> a/b test.</p>

<p>Given these tables, write a query to display a graph to understand how unsubscribes are affecting login rates over time.</p>

<p><em>Note: Let’s say that all users are automatically put into the A/B test.</em></p>

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

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

<p><code>events</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>action</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

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

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


Write a query to display a graph to understand how unsubscribes are affecting login rates over time.

New Notification

<p>Let’s say that you’re working on a job recommendation engine. You have access to all user Linkedin profiles, a list of jobs each user applied to, and answers to questions that the user filled in about their job search.</p>

<p>Using this information, how would you build a job recommendation feed?</p>


<p>What problem can arise in job recommendation systems with regard to initial recommendations?</p>

What problem can arise in job recommendation systems with regard to initial recommendations?

Job Recommendation

<p>We’re given two tables, a table of <code>notification_deliveries</code> and a table of <code>users</code> with <code>created</code> and purchase <code>conversion dates</code>. If the user hasn’t purchased then the <code>conversion_date</code> column is <code>NULL</code>.</p>

<p>Write a query to get the distribution of total push notifications before a user converts.</p>

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

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

<p><code>notification_deliveries</code> table</p>

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

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

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

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

<tr>
<td><code>conversion_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>total_pushes</code></td>
<td>INTEGER</td>
</tr>

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


Twitter Interview Questions

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