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Institute for Defense Analyses Interview Questions

Institute for Defense Analyses Interview Guides

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

Machine Learning

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

Softmax vs Logistic

Classification and Regression

Business Case

How would you create a policy for refunds with regards to balancing customer sentiment and goodwill versus revenue tradeoffs?

Food Delivery Refund Policy

Vision Setting and Execution Strategy

A/B Testing

Extra Delivery Pay

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

Success Measurement

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

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


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


Describing a real-world data cleaning and organization project

Data Cleaning Experiences

Data Pipelines

<p>What are the key differences between classification models and regression models?</p>


<p>What is the MOST important difference between regression and classification models?</p>


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

Classification vs Regression

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


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

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

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


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


<p>What are the logistic and softmax functions? What is the difference between the two?</p>

<p>What makes them useful for use in logistic regression?</p>


<p>In logistic regression, how is the predicted class determined based on the logistic function?</p>


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

Softmax vs Logistic II

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


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

Softmax vs Logistic I

<p>Let’s say you work at a food delivery company.</p>

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


<p>Let’s say you work at a food delivery startup.</p>

<p>The customer success team is asking for a standardized refund policy for the company after historically processing each case differently.</p>

<p>How would you create a policy for refunds with regards to balancing customer sentiment and goodwill versus revenue tradeoffs?</p>


<p>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.</p>

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

<p><em>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></em>.</p>

<h3><strong>Example:</strong></h3>

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

<p>For simplicity, consider two years: 2021 and 2022.</p>

<p><code>sales_2021</code> table</p>

<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>
<p><code>sales_2022</code> table</p>

<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>
<p><strong>Output:</strong></p>

<p><code>sales_pivot</code> table</p>

<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>
<p>This output pivot table shows the total sales for each branch, broken down by year.</p>


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

Branch Sales Pivot

<p>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.</p>

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


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

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

Institute for Defense Analyses Interview Questions

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