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Doma Interview Questions

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A/B Testing

Experiment Validity

Delivery Estimate Model

A/B Test Power Size

Green Dot

Delivery Online

Machine Learning

Decision Tree Evaluation

Spam Classifier 

Random Forest Explanation

Xgboost vs Random Forest

Product Sense & Metrics

Group Success

Instagram TV Success

Measure Facebook Stories success by tracking reach, engagement, and actions aligned with specific business goals

Facebook Story Success

Data Structures & Algorithms

Given a list of strings, write a Python program to check whether each string has all the same characters or not.

Same Characters

Write a function data_stream_median to calculate the median from a stream of integers.

Data Stream Median

Tower of Hanoi

Statistics

P-value to a Layman

What are the assumptions of linear regression?

Assumptions of Linear Regression

Find a bound for how many people drink coffee AND tea based on a survey

Bounds for Coffee and Tea Drinkers

When an interviewer asks a question along the lines of:

<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>

How would you respond?

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

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

Your Strengths and Weaknesses I

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

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

Your Strengths and Weaknesses II

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

Your Strengths and Weaknesses

Brainteasers

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

What are the assumptions of linear regression?

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

Regression assumptions

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>

Select the 2nd highest salary in the engineering department

2nd Highest Salary

Explain the difference between the XGBoost and random forest algorithms and give an example where you would use one over the other.

Why might a data scientist choose to use XGBoost instead of Random Forest for a particular machine learning task?

Why might a data scientist choose to use XGBoost instead of Random Forest for a particular machine learning task?

XGBoost vs Random Forest: Choice

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

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

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

Average Trees

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 you work as a data scientist at a bank.

You are tasked with building a decision tree model to predict if a borrower will pay back a personal loan they are taking out.

<ol>
<li>How would you evaluate whether using a decision tree algorithm is the correct model for the problem?</li>

<li>Let’s say you move forward with the decision tree model. How would you evaluate the performance of the model before deployment and after?</li>
</ol>

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

Let’s say you’re analyzing an AB test that has both a test group and a control group.

<ol>
<li>How do you calculate the sample size necessary for an accurate measurement?</li>

<li>Let’s say that the sample size is similar and sufficient between the two groups. In order to measure very small differences between the two, should the power get bigger or smaller?</li>
</ol>

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

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

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

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

Delivery Estimate Model I

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

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 measure the success of Facebook Groups?

Considering the purpose of Facebook Groups as a platform for connecting users through shared interests or real-life relationships, which metrics would be appropriate to measure the success of these groups?

Considering the purpose of Facebook Groups as a platform for connecting users through shared interests or real-life relationships, which metrics would be appropriate to measure the success of these groups?

Let’s say you’re a Product Data Scientist at Instagram. How would you measure the success of the Instagram TV product?

What is the primary goal of Instagram TV as a product feature?

What is the primary goal of Instagram TV as a product feature?

Let’s say you are tasked with building a spam classifier for emails. Assume that you’ve built a V1 of the model.

What metrics would you use to track accuracy and validity of the model?

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.

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

How would you analyze how the feature is performing?

How would you analyze how the feature is performing?

Recruiting Leads

Analytics

Three zebras are chilling in the desert. Suddenly a lion attacks.
Each zebra is sitting on a corner of a triangle with sides of equal length.
Each zebra randomly picks a direction and only runs along the outline of the triangle to either edge of the triangle.

What is the probability that none of the zebras collide?

Three zebras are chilling in the desert. Suddenly a lion attacks.

Each zebra is sitting on a corner of a triangle with side of equal length. Each zebra randomly picks a direction and only runs along the outline of the triangle to either edge of the triangle.

What is the probability that none of the zebras collide?

Three zebras are chilling in the desert. Suddenly a lion attacks.

Each zebra is sitting on a corner of a triangle with side of equal length.  Each zebra randomly picks a direction and only runs along the outline of the triangle to either edge of the triangle.

What is the probability that none of the zebras collide?



Three Zebras

Let’s say we’re working on a new feature for LinkedIn chat. We want to implement a green dot to show an “active user” but given engineering constraints, we can’t AB test it before release.

How would you analyze the effectiveness of this new feature?

Let’s say we want to build a new algorithm for Lyft Line.

How should we test it, measure success of the test, and eventually roll it out?

Building Lyft Line

Let’s say you work at Spotify.

We want to design a relational database for storing metadata about songs.

We want to include metadata like song title, song length, the date the song was added to the platform, artist, album, track number (on the album), the song’s release year, and its genre.

How would you go about designing this database?

Music Database

Data Modeling

Given a list of strings, write a Python program to check whether each string has all the same characters or not. What is the complexity of this program?

<h3>Example</h3>

Input:

<pre tabindex="0" class="chroma"><code>string_list = [&#39;bbbbb&#39;, &#39;abc&#39;, &#39;aaaaaaaab&#39;]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def same_characters(input_list) -&gt; False
</code></pre>

Explanation:

<ul>
<li><code>string bbbbb</code> has all the same characters 
</li>
<li><code>string abc</code> does not have all the same characters 
</li>
<li><code>string aaaaaaaab</code> does not have all the same characters</li>
</ul>

How would you measure success for Facebook Stories?

Write a function <code>data_stream_median</code> to calculate the new median from a stream of ordered integers and the new element which is not yet inserted into the stream.

The median is the middle value in an ordered integer list. If the size of the list is even, there is no middle value, so the median is the mean of the two middle values.

Example:

<pre tabindex="0" class="chroma"><code>new_value = 2
stream = [1, 2, 3, 4, 5, 6]
def data_stream_median(new_value, stream): -&gt; 3
</code></pre>

How would you decide whether or not to create a product, like a job board, for Facebook?

Imagine Facebook is creating a job board. How would you design an A/B test to evaluate its effectiveness?

Assessing the market potential and then use A/B testing to measure its effectiveness against user behavior

Facebook Job Board Design

Tower of Hanoi is a fun puzzle game that consists of a set of <code>3</code> pegs (<code>A</code>, <code>B</code>, <code>C</code>) and <code>n</code> number of disks. You are required to move all disks from the source peg <code>A</code> to destination peg <code>C</code>, under the following conditions:

<ul>
<li>You can only move one disk for each action.</li>
<li>You can only move the disk onto the top of another peg; you cannot place it off to the side or under existing disks.</li>
<li>You cannot place a larger disk onto a smaller disk.</li>
</ul>

Initially, all disks are on the source <code>A</code> peg and sorted by decreasing width from bottom to the top (widest on the bottom, smallest on the top).

You must develop an algorithm to move all disks from <code>A</code> to the destination peg <code>C</code> with the optimal solution. Also, return every step made from the starting state to the final state.

<img src="https://i.ibb.co/my0Vm13/initail.png" alt="alt"/>

<img src="https://i.ibb.co/0Ftzs7D/final.png" alt="alt"/>

Example

Input:

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

Output:

<pre tabindex="0" class="chroma"><code>#return list of {&#34;A&#34;:[],&#34;B&#34;:[],&#34;C&#34;:[]} 
tower_of_hanoi_solver(n) -&gt; [
 {&#34;A&#34;: [1, 2, 3], &#34;B&#34;: [], &#34;C&#34;: []},
 {&#34;A&#34;: [2, 3], &#34;B&#34;: [], &#34;C&#34;: [1]},
 {&#34;A&#34;: [3], &#34;B&#34;: [2], &#34;C&#34;: [1]},
 {&#34;A&#34;: [3], &#34;B&#34;: [1, 2], &#34;C&#34;: []},
 {&#34;A&#34;: [], &#34;B&#34;: [1, 2], &#34;C&#34;: [3]},
 {&#34;A&#34;: [1], &#34;B&#34;: [2], &#34;C&#34;: [3]},
 {&#34;A&#34;: [1], &#34;B&#34;: [], &#34;C&#34;: [2, 3]},
 {&#34;A&#34;: [], &#34;B&#34;: [], &#34;C&#34;: [1, 2, 3]}
 ]
</code></pre>

What is the minimal number of steps needed to solve the Tower of Hanoi problem with n disks?

What is the minimal number of steps needed to solve the Tower of Hanoi problem with *n* disks?

Linear Data Structures

Let’s say we’re building a new feature that tells dashers when they should go online or not in order to meet delivery demand. 

How would you test whether the feature was working successfully?

Let’s say that you work for an E-commerce store. A new marketing manager joins the company and redesigns the existing new-user email journey to try and boost customer conversion rates. A few weeks after launching the new email journey, the new-user to customer conversion rate goes up from 40% to 43%.

Before you can celebrate, the company’s CMO points out a troubling fact. Just a few months prior to the new manager starting the conversion rate already stood at 45%, before slowly dropping down to the “starting” 40%.

How would you investigate if the redesigned email campaign actually led to the increase in the conversion rate, and that the increase wasn’t instead the result of other factors?

What would be an appropriate method to investigate whether the redesigned email campaign led to an increase in the conversion rate of an E-commerce store, in the absence of infrastructure for an AB test?

What would be an appropriate method to investigate whether the redesigned email campaign led to an increase in the conversion rate of an E-commerce store, in the absence of infrastructure for an AB test?

Causal Email Journey

How would you find out if an increase in user conversion rates after a new email journey is casual or just part of a wider trend?

Causal Email Journey 

A survey asked 100 respondents two questions:

<ol>
<li>Do you like tea?</li>
<li>Do you like coffee?</li>
</ol>

70% of respondents said they liked coffee, and 80% of the respondents said they liked tea. Only 10% of respondents said they liked neither.

Based on this survey, what are the upper and lower bounds for the proportion of the population that like tea and coffee?

Given that 70% of people like dogs, 60% like cats, and only 10% dislike both, what is the proportion of people who like both dogs and cats?

Given that 70% of people like dogs, 60% like cats, and only 10% dislike both, what is the proportion of people who like both dogs and cats?

Bounds for Coffee and Tea Drinkers I

In a survey with 100 respondents, 80% like reading, 70% enjoy sports, and 10% dislike both. Using a 95% confidence interval, what are the lower and upper bounds of the proportion of respondents who like both reading and sports?

In a survey with 100 respondents, 80% like reading, 70% enjoy sports, and 10% dislike both. Using a 95% confidence interval, what are the lower and upper bounds of the proportion of respondents who like both reading and sports?

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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