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Machine Learning

Encoding Categorical Features

Food Delivery Times

Decision Tree Evaluation

How to model merchant acquisition in a new market?

Merchant Acquisition

Xgboost vs Random Forest

Product Sense & Metrics

Group Success

Instagram TV Success

Amateur Performance

Docs Metrics

WhatsApp Metrics

Analytics

Describing a data project and its challenges

Hurdles In Data Projects

Strategically resolving misaligned expectations with stakeholders for a successful project outcome

Stakeholder Communication

Making data-driven insights actionable for those without technical expertise

Simple Explanations

Brainteasers

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

Data Pipelines

Design a data pipeline for hourly user analytics.

Data Pipelines and Aggregation

Let's say that you're in charge of getting payment data into your internal data warehouse. 

Payment Data Pipeline

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

<ul>
<li>Why did you apply to our company?</li>
<li>What are you looking for in your next job?</li>
<li>What makes you a good fit for our company?</li>
</ul>

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


<p>When asked 'What are you looking for in your next job?' in an interview, how can you tie the company's employee benefits into your response?</p>

When asked 'What are you looking for in your next job?' in an interview, how can you tie the company's employee benefits into your response?

Why Do You Want to Work With Us I

<p>How can company values be used effectively in an interview when asked 'What makes you a good fit for our company?'</p>

How can company values be used effectively in an interview when asked 'What makes you a good fit for our company?'

Why Do You Want to Work With Us II

<p>When responding to the question 'Why did you apply to our company?' during an interview, what aspect should you highlight?</p>

When responding to the question 'Why did you apply to our company?' during an interview, what aspect should you highlight?

Why Do You Want to Work With Us III

<p>Describe a data project you worked on. What were some of the challenges you faced?</p>


<p>How would you handle the data preparation for building a machine learning model using imbalanced data?</p>


Addressing imbalanced data in machine learning through carefully prepared techniques.

Data Preparation for Imbalanced Data

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


<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>


Select the 2nd highest salary in the engineering department

2nd Highest Salary

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


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


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

XGBoost vs Random Forest: Choice

<p>Let’s say you are working on Google Docs. A product manager comes to you and asks how the product is doing. </p>

<p>What are the top five metrics that you would start tracking to understand the health of Google Docs?</p>


<p>How would you convey insights and the methods you use to a non-technical audience?</p>


<p>Let’s say you work as a data scientist at a bank.</p>

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

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

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


<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>


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

<p>How would you measure the success of Facebook Groups?</p>


<p>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?</p>


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?

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


<p>What is the primary goal of Instagram TV as a product feature?</p>

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

<p>Let’s say you have analytics data stored in a data lake. An analyst tells you they need hourly, daily, and weekly active user data for a dashboard that refreshes every hour.</p>

<p>How would you build this data pipeline?</p>


<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>Describe an analytics experiment that you designed. How were you able to measure success?</p>


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

Success Measurement

A/B Testing

<p>Let’s say you have a categorical variable with thousands of distinct values, how would you encode it?</p>


<p>Which method can be used to extract communities from large networks, that does not require a pre-determined number of clusters like K-means?</p>

Which method can be used to extract communities from large networks, that does not require a pre-determined number of clusters like K-means?

<p>Let’s say that you’re a data scientist at DoorDash.</p>

<p>How would you build a model to predict which merchants the company should go after for acquisition when entering a new market?</p>


<p>Let’s say that you’re in charge of getting payment data into your internal data warehouse.</p>

<p>How would you build an ETL pipeline to get Stripe payment data into the database so analysts can build revenue dashboards and run analytics?</p>


<p>Let’s say you work as a data scientist at DoorDash. </p>

<p>You are tasked to build a machine learning system that minimizes missing or wrong orders placed on the app.</p>

<p>How would you go about designing this system?</p>


Minimize Wrong Orders

<p>You work as a machine learning engineer for a health insurance company. Design a machine learning model, which given a set of health features, classifies if the individual will undergo major health issues or not.</p>


Creating a machine learning model for evaluating a patient's health

Risk Assessment Model

<p>What are some effective ways to make data more accessible to non-technical people?</p>


Demystifying data for non-technical users through visualization and clear communication

Accessible Data

Data Viz & Interpretation

<p>To improve customer experience on Uber Eats, what key parameters would you focus on improving?</p>


Delivering an exceptional customer experience by focusing on key customer-centric parameters

Uber Eats Customer Experience

<p>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.</p>

<p>How would you analyze the effectiveness of this new feature?</p>


Green Dot

<p>How would you measure success for Facebook Stories?</p>


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

Facebook Story Success

<p>Let’s say you’re a data scientist working on pricing different products on our ecommerce site. The online price is dependent on the availability of the product, the demand, and the logistics cost of providing it to the end consumer. </p>

<p>You discover our algorithm is vastly under-pricing a certain consumer product. What are the steps you take in diagnosing the problem?</p>


Underpricing Algorithm

Business Case

<p>Let’s say that you’re a data scientist working for Facebook.</p>

<p>You’ve been asked to generate a machine learning model that can map the legal first name of a person to likely nicknames they might have.</p>

<p>How do you go about designing this model?</p>


Mapping Nicknames

<p>Let’s say that a basketball team, e.g., the LA Lakers, has hired you as a data scientist to scout for potential players. Your job is to identify similar basketball players, cluster them in smaller groups, and have them practice with each other based on their strengths and weaknesses.</p>

<p>You train a clustering model to group similarly scouted players together.</p>

<p>How would you assess if your algorithm worked by placing similar players in the same groups without pre-labeled data in hand?</p>


Clustering Basketball Players

<p>You are a data scientist at YouTube focused on creators.</p>

<p>A PM comes to you worried that amateur video creators could do well before but now it seems like only “superstars” do well.</p>

<p>What data points and metrics would you look at to decide if this is true or not?</p>


<p>Let’s say you’re a data scientist on the marketing team for Spotify. How would you determine how much Spotify should pay for an ad in a third party app?</p>


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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