Prepare for and practice interview questions from The wonderful company.

The wonderful company Interview Questions

<p>headquartered in los angeles, the wonderful company is a privately held $4 billion global company dedicated to harvesting health and happiness around the world through its iconic consumer brands. the company’s 9,000 employees worldwide are dedicated to bringing consumers everywhere the freshest, most wholesome pistachios, almonds, citrus and pomegranates; bottling the finest water and wines; and creating colorful bouquets that are sure to touch the heart. this commitment is reflected in the company’s market share: wonderful pistachios is america’s no. 1 tree nut brand and one of the top-selling salty snacks; wonderful halos is the no. 1 mandarin orange in america; pom wonderful is the no. 1 100% pomegranate brand in america; fiji water is america's no. 1 premium bottled water brand; teleflora is the no. 1 floral delivery service through local florists; and justin wine has the no. 1 cabernet sauvignon in california. a 2016 nielsen study evaluating the familiarity, quality, and momentum</p>

headquartered in los angeles, the wonderful company is a privately held $4 billion global company dedicated to harvesting health and happiness around the world through its iconic consumer brands. the company’s 9,000 employees worldwide are dedicated to bringing consumers everywhere the freshest, most wholesome pistachios, almonds, citrus and pomegranates; bottling the finest water and wines; and creating colorful bouquets that are sure to touch the heart. this commitment is reflected in the company’s market share: wonderful pistachios is america’s no. 1 tree nut brand and one of the top-selling salty snacks; wonderful halos is the no. 1 mandarin orange in america; pom wonderful is the no. 1 100% pomegranate brand in america; fiji water is america's no. 1 premium bottled water brand; teleflora is the no. 1 floral delivery service through local florists; and justin wine has the no. 1 cabernet sauvignon in california. a 2016 nielsen study evaluating the familiarity, quality, and momentum 

Overview

The wonderful company Interview Guides

Write a query to select the top 3 departments with at least ten employees and rank them according to the percentage of their employees making over 100K in salary.

Employee Salaries

Cumulative Distribution

Given a users table, write a query to get the cumulative number of new users added by the day, with the total reset every month. 

Cumulative Reset

Machine Learning

PCA and K-Means

Restaurant Recommender

Area Under the ROC Curve

Behavioral

Strategically resolving misaligned expectations with stakeholders for a successful project outcome

Stakeholder Communication

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

Your Strengths and Weaknesses

Statistics

What are the assumptions of linear regression?

Assumptions of Linear Regression

Product Sense & Metrics

WhatsApp Metrics

Challenge

<p>When an interviewer asks a question along the lines of:</p>

<ul>
<li>What would your current manager say about you? What constructive criticisms might he give?</li>
<li>What are your three biggest strengths and weaknesses you have identified in yourself?</li>
</ul>

<p>How would you respond?</p>


<p>When asked about your strengths in an interview, what is an effective way to respond?</p>

When asked about your strengths in an interview, what is an effective way to respond?

Your Strengths and Weaknesses I

<p>Which of the following is an acceptable strategy when discussing weaknesses in an interview?</p>

Which of the following is an acceptable strategy when discussing weaknesses in an interview?

Your Strengths and Weaknesses II

<p>Given a <code>employees</code> and <code>departments</code> table, select the top 3 departments with at least ten employees and rank them according to the percentage of their employees making over 100K in salary.</p>

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

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

<p><code>employees</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>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>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>
<p><strong>Output:</strong></p>

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

<tbody>
<tr>
<td><code>percentage_over_100k</code></td>
<td>FLOAT</td>
</tr>

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

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


<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

<p>Talk about a time when you had trouble communicating with stakeholders. How were you able to overcome it?</p>


<p>Given the two tables, write a SQL query that creates a cumulative distribution of the number of comments per user. Assume bin buckets class intervals of one.</p>

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

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

<p><code>users</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>

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

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

<tr>
<td><code>sex</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
<p><code>comments</code> table</p>

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

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

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


<p>Given a <code>users</code> table, write a query to get the cumulative number of new users added by the day, with the total reset every month. </p>

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

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

<p><code>users</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>

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

<table>
<thead>
<tr>
<th>DATE</th>
<th>INTEGER</th>
</tr>
</thead>

<tbody>
<tr>
<td>2020-01-01</td>
<td>5</td>
</tr>

<tr>
<td>2020-01-02</td>
<td>12</td>
</tr>

<tr>
<td>…</td>
<td>…</td>
</tr>

<tr>
<td>2020-02-01</td>
<td>8</td>
</tr>

<tr>
<td>2020-02-02</td>
<td>17</td>
</tr>

<tr>
<td>2020-02-03</td>
<td>23</td>
</tr>
</tbody>
</table>


<p>What’s the relationship between PCA and K-means clustering?</p>


<p>What does the variable “k” in k-means clustering refer to?</p>


What does the variable "k" in k-means clustering refer to?

Input of K-means

<p>What do you think are the most important metrics for WhatsApp?</p>


<p>What is the optimal strategy for reducing customer churn rate in a messaging platform like WhatsApp?</p>


What is the optimal strategy for reducing customer churn rate in a messaging platform like WhatsApp?

<p>Let’s say that you’re working at a global trading company and you’re analyzing the price of a particular asset over time. This dataset is super noisy, volatile, and you’re not guaranteed completely accurate data.</p>

<p>How would you analyze this data to ensure there aren’t any discrepancies?</p>


Time Series Discrepancies

Forecasting & Time Series

<p>How would you build a restaurant recommender on Facebook?</p>

<p>Start with how you would go about getting this data, then talk about how you would build it.</p>

<p>What are some downfalls or worries about adding this feature to Facebook?</p>


<p>Suppose you are given three models for a binary classification problem. Each model gives you a probability of an input belonging to class 1.</p>

<p>You are asked to build an area under the ROC curve metric to evaluate the model performance. Briefly explain how you will do that.</p>

<p>After you make the metric and make sure it works correctly, you apply it on three models and get the following results:</p>

<ul>
<li>Model 1: 0.1</li>
<li>Model 2: 0.5</li>
<li>Model 3: 0.8</li>
</ul>

<p>Briefly explain your evaluation of these models and choose one to use for the classifier.</p>


<p>Let’s say you manage a hardware store and need to order snow shovels in Q3, aiming to have zero inventory left by the end of winter. Last year, during a mild winter, you sold 120 shovels at $20 each, but in harsher years, sales have reached up to 400.</p>

<p>How would you estimate the number of shovels to order and set the price for a mild winter, given your goal of selling out by season’s end?</p>


How would you decide how many snow shovels to order and what price to set to sell out during a mild winter?

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

The wonderful company Interview Questions

Overview

The wonderful company Interview Guides

Challenge

The wonderful company Interview Questions

Discussion & Interview Experiences

Discussion & Interview Experiences