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Southwest Research Institute Interview Questions

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Machine Learning

Encoding Categorical Features

Coefficients of Logistic Regression

What are the logistic and softmax functions? What is the difference between the two?

Softmax vs Logistic

Spam Classifier 

Classification and Regression

Behavioral

Strategically resolving misaligned expectations with stakeholders for a successful project outcome

Stakeholder Communication

Describing a data project and its challenges

Hurdles In Data Projects

How would you prepare and monitor a churn model before and after production deployment?

Model Deployment Pipeline

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

Your Strengths and Weaknesses

How would you answer when an Interviewer asks why you applied to their company?

Why Do You Want to Work With Us

Statistics

P-value to a Layman

What are the assumptions of linear regression?

Assumptions of Linear Regression

Multicollinearity in Regression

Product Sense & Metrics

Increasing Group Comments

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

Success Measurement

Vision Setting and Execution Strategy

A/B Testing

Experiment Validity

Network Experiment Design

Extra Delivery Pay

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 want to test the close friends feature on Instagram Stories.

How would you make a control group and test group to account for network effects?

What could be a potential risk when Facebook segments the metrics of the user interface change by market or demographic groups?

What could be a potential risk when Facebook segments the metrics of the user interface change by market or demographic groups?

Network Experiment Design I

What is the primary metric that Facebook should monitor if it decides to make the user interface of its posting feature more like Instagram's?

What is the primary metric that Facebook should monitor if it decides to make the user interface of its posting feature more like Instagram's?

Network Experiment Design II

If Facebook changes its user interface to mimic Instagram's, which adverse effect should they anticipate and monitor?

If Facebook changes its user interface to mimic Instagram's, which adverse effect should they anticipate and monitor?

Network Experiment Design III

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

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

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

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

You’re a data scientist at YouTube. Leadership wants to revisit how the platform measures success, not for a specific new feature, but for the product as a whole given its current state.

How would you define and measure success for YouTube? Identify your primary and secondary metrics, explain your rationale for each, and discuss how you would choose the right thresholds for any engagement-based metrics you propose.

How would you interpret coefficients of logistic regression for categorical and boolean variables?

Why is one-hot encoding recommended for categorical variables in logistic regression models?

Why is one-hot encoding recommended for categorical variables in logistic regression models?

What are the logistic and softmax functions? What is the difference between the two?

What makes them useful for use in logistic regression?

In logistic regression, how is the predicted class determined based on the logistic function?

In logistic regression, how is the predicted class determined based on the logistic function?

Softmax vs Logistic II

What is the key characteristic of the logistic function that makes it useful for mapping continuous values to a probability?

What is the key characteristic of the logistic function that makes it useful for mapping continuous values to a probability?

Softmax vs Logistic I

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

Addressing imbalanced data in machine learning through carefully prepared techniques.

Data Preparation for Imbalanced Data

Let’s say you’ve just finished building a churn prediction model for a subscription service, and the team is considering deploying it to automatically trigger retention emails for users at risk of leaving.

How would you ensure this model is ready for production, and what steps would you take to monitor its performance after launch?

What are the key differences between classification models and regression models?

What is the MOST important difference between regression and classification models?

What is the MOST important difference between regression and classification models?

Classification vs Regression

Let’s say we’ve built a churn prediction model for a subscription service using user behavior data from the past 12 months, and now we want to deploy it to production and also apply it to a new user segment that wasn’t in our original training data.

How would you approach preparing the model for deployment and ensuring it generalizes well to the new dataset?

How would you get a model ready for production use and adaptation to new datasets?

Model Deployment Preparation

ML Ops

You are given a singly linked list, write a function to find and return the last node of the list. If the list is empty, return null.

Write a function to find and return the last node of a singly linked list. If the list is empty, return null.

Last Element of a Singly Linked List

Data Structures & Algorithms

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?

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

When an interviewer asks you a question along the lines of:

<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>

How should you respond?

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?

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

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

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

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

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

How would you tackle multicollinearity in multiple linear regression?

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

Tell me about a data project that didn’t go the way you expected. What did you set out to do, what surprised you, and how did you handle it?

Describe a time when you had to define a long-term vision for a project or team and move it from concept to reality.

Interviews for leadership or senior technical roles look for more than just “finishing a project.” Your answer should specifically address:

<ol>
<li>The “Why”: What data or organizational gap necessitated this vision?</li>
<li>The Framework: How did you translate a high-level goal into a roadmap?</li>
<li>The Friction: How did you handle stakeholders or team members who were skeptical of the new direction?</li>
</ol>

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.

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

Risk Assessment Model

Tell me about a project in which you had to clean and organize a large dataset.

Describing a real-world data cleaning and organization project

Data Cleaning Experiences

Analytics

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

Making data-driven insights actionable for those without technical expertise

Simple Explanations

Your company, a multinational retail corporation, has been storing sales data from various branches worldwide in separate tables according to the year the sales were made. The current data structure is proving inefficient for business analytics and the management has requested your expertise to streamline the data.

Write a query to create a pivot table that shows total sales for each branch by year.

Note: Assume that the sales are represented by the <code>total_sales</code> column and are in USD. Each branch is represented by its unique <code>branch_id</code>.

<h3>Example:</h3>

Input:

For simplicity, consider two years: 2021 and 2022.

<code>sales_2021</code> table

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

<tbody>
<tr>
<td>id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>branch_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>total_sales</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>sales_2022</code> table

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

<tbody>
<tr>
<td>id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>branch_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>total_sales</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
Output:

<code>sales_pivot</code> table

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

<tbody>
<tr>
<td>branch_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>total_sales_2021</td>
<td>INTEGER</td>
</tr>

<tr>
<td>total_sales_2022</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
This output pivot table shows the total sales for each branch, broken down by year.

Write a query to create a pivot table that shows total sales for each branch by year

Branch Sales Pivot

Let’s say you work at a food delivery company.

How would you measure the effectiveness of giving extra pay to delivery drivers during peak hours to meet the demand from consumers?

Let’s say you work on Facebook Groups. 

How would you go about increasing the number of comments on each Group post?

You are tasked with flagging users who post fake comments on Amazon to then give to the modeling team for further analysis.  

<ol>
<li>How would you initially go about filtering users who post fake comments on Amazon?</li>

<li>Let’s say that the team needs more data points faster. How would you scale out the effort with minimal manual intervention?</li>
</ol>

Flagging Users

Business Case

Let’s say there are two tables, <code>students</code> and <code>tests</code>.

The <code>tests</code> table doesn’t have a student id. However, it has the first and last name and date of birth, which can be inaccurate because these details are entered manually.

What process would you use to determine which student in the student rosters took which exam?

Notes: You can assume that you can utilize a human to support reviewing your matches and that you need to evaluate thousands of rows of data.

Example:

Input:

<code>students</code> table

<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>firstname</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>lastname</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>date_of_birth</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
Output:

<code>tests</code> table

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

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

<tr>
<td><code>lastname</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>date_of_birth</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>test_score</code></td>
<td>INTEGER</td>
</tr>

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

Student Tests

Data Modeling

Let’s say you’re an ML engineer at Netflix. You have access to reviews of 10K movies. Each review contains multiple sentences along with a score ranging from 1 to 10.

How would you design an ML system to predict the movie score based on the review text?

Score Based on Review

How would you build a database for a consumer file storage company like Dropbox?

Note: The database must be able to store many different file type formats and keep updates and history of file changes.

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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