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Thrivent Interview Questions

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Machine Learning

Booking Regression

Missing Housing Data

Lasso vs Ridge

Bagging vs Boosting

Random Forest Explanation

Statistics

P-value to a Layman

What are the assumptions of linear regression?

Assumptions of Linear Regression

Correlation in Regression

What is the difference between type I and type II errors?

Type I and II Errors

Multicollinearity in Regression

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

Select the 2nd highest salary in the engineering department

2nd Highest Salary

Duplicate Rows

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

Branch Sales Pivot

How would you design a data warehouse for a e-commerce company looking to expand internationally?

International e-Commerce Warehouse

Probability

Different Card

Scalped Ticket

Poker Pair

What's the probability that the second card is not an ace?

Second Ace

The use of Martingale strategy for finance and online advertising

Martingale Strategy

Behavioral

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

Why Do You Want to Work With Us

Describing a data project and its challenges

Hurdles In Data Projects

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

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

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

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 that you’re training a classification model.

How would you combat overfitting when building tree-based models?

Let's say that you're training a classification model.   How would you combat overfitting when building tree-based models?

Overfit Avoidance

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 we’re comparing two machine learning algorithms. In which case would you use a bagging algorithm versus a boosting algorithm? 

Give an example of the tradeoffs between the two.

In machine learning, when would you use a bagging algorithm over a boosting algorithm?

In machine learning, when would you use a bagging algorithm over a boosting algorithm?

Bagging vs. Boosting

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

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>

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

Xgboost vs Random Forest

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

What is the difference between Logistic and Linear Regression?

When would use one instead of the other in practice?

What is the difference between Logistic and Linear Regression?

Linear vs Logistic Regression

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

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

Classification and Regression

Let’s say you work at Allstate. Allstate is running <code>N</code> online ads right now. The table <code>ads</code> contains all those ads, ranked by popularity via the <code>id</code> column (e.g., the entry with <code>id = 1</code> is the most popular, etc.).

Create a subquery or common table expression named <code>top_ads</code> containing the top 3 ads (by popularity) and return the number of rows that would result from the following operations

<ol>
<li><code>ads INNER JOIN top_ads</code></li>
<li><code>ads LEFT JOIN top_ads</code></li>
<li><code>ads RIGHT JOIN top_ads</code></li>
<li><code>ads CROSS JOIN top_ads</code></li>
</ol>

Note: Please make the <code>join_type</code> column in your output have the values <code>inner_join</code>, <code>left_join</code>, etc. for each of their respective join types

Note: Please return only one query with each number in a different row

Example:

Input:

<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>join_type</code></td>
<td>VARCHAR</td>
</tr>

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

Size of Joins

What’s the difference between Lasso and Ridge Regression?

Under what circumstances is it recommended to use Lasso regression over Ridge regression?

Under what circumstances is it recommended to use Lasso regression over Ridge regression?

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

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

Docs Metrics

Product Sense & Metrics

What’s the relationship between PCA and K-means clustering?

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

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

Input of K-means

PCA and K-Means

In the context of hypothesis testing, what are type I errors (type one errors) and type II errors (type two errors)? What is the difference between the two?

Bonus: Describe the probability of making each type of error mathematically.

How would you tackle multicollinearity in multiple linear regression?

How do you detect and handle correlation between variables in linear regression? What will happen if you ignore the correlation in the regression model?

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>

Vision Setting and Execution Strategy

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.

Example:

Input:

<code>employees</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>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>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>
Output:

<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>

Given a <code>users</code> table, write a query to return only its duplicate rows.

Example:

Input:

<code>users</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>

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

We want to build a model to predict housing prices in the city of Seattle. We’ve scraped 100K sold listings over the past three years but found that around 20% of the listings are missing square footage data.

How do we deal with the missing data to construct our model?

We want to build a model to predict housing prices in the city of Seattle. We’ve scraped 100K sold listings over the past three years, but have discovered that around 20% of the listings are missing square footage data.

How would you approach dealing with this missing data, in order to construct the most useful predictive model possible?

We want to build a model to predict housing prices in the city of Seattle. We’ve scraped 100K sold listings over the past three years, but have discovered that around 20% of the listings are missing square footage data.

How would you approach dealing with this missing data, in order to construct the most useful predictive model possible?



How would you explain the concept of linear regression to three different audiences: a child, a first-year college student, and a seasoned mathematician? Ensure your explanations are tailored to the understanding level of each audience.

Describe linear regression to various audiences with different levels of knowledge.

Explaining Linear Regression to Different Audiences

How would you choose the k value when using k-means clustering?

choosing k value during k-means clustering

Choosing k

You are given a dictionary with two keys <code>a</code> and <code>b</code> that hold integers as their values.

Without declaring any other variable, swap the value of <code>a</code> with the value of <code>b</code> and vice versa.

Note: Return the dictionary after editing it.

Example:

Input:

<pre tabindex="0" class="chroma"><code>numbers = {
 &#39;a&#39;:3,
 &#39;b&#39;:4
}
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def swap_values(numbers) -&gt; {&#39;a&#39;:4,&#39;b&#39;:3}
</code></pre>

Swap Variables

Data Structures & Algorithms

Let’s say you work for an e-commerce company. Vendors can send products to the company’s warehouse to be listed on the website. Users are able to order any in-stock products and submit returns for refunds if they’re not satisfied.

The front end of the website includes a vendor portal that provides sales data in daily, weekly, monthly, quarterly, and yearly intervals.

The company wants to expand worldwide. They put you in charge of designing its end-to-end architecture, so you need to know what significant factors you’ll need to consider. What clarifying questions would you ask?

What kind of end-to-end architecture would you design for this company (both for ETL and reporting)?

Challenge

Thrivent Salaries by Position

<div><h2>Senior Research Analyst I High-Yield</h2>The Senior Research Analyst I High-Yield is the senior-most research analyst responsible for independent research covering a particular industry. This role analyzes and recommends the purchase and sale of public high yield corporate bonds and related securities within the analysts assigned industries. Analysts at the Senior I level are highly independent and expected to proactively suggest investment decisions and understand existing investments, credit risk, and industry nuances at an expert level with highly consistent outcomes. In addition, the Senior I Research Analyst makes relative weighting and relative value recommendations within the high yield credit market. Senior I research analysts may mentor research analysts and are sought after as experts in the industries they cover across the organization. Success in this role requires working well in a team environment, while being highly independent and consistently providing value enhancing recommendations to portfolio managers that add significant value to the portfolio. The Research function is responsible for conducting research analyses on specific organizations, securities, financial products, and the overall economic environment.<h3>Duties & Responsibilities:</h3><ul><li>Perform independent, fundamental credit analysis on issuers within assigned industries. Has strong understanding of assigned credits/industries or has the ability to quickly ramp on new coverage.</li><li>Analyze company financial statements from a bondholder's perspective to develop an opinion of the company's operational strengths, weaknesses, and directional outlook.</li><li>Develop and maintain financial models to evaluate credit worthiness.</li><li>Prepare detailed credit reports and provide relative value opinions, which lead to portfolio recommendations.</li><li>Propose novel suggestions indicative of expert knowledge of industries covered.</li><li>Demonstrates ability and desire to have a broader impact within the credit research team and the larger investment organization.</li><li>Demonstrates a track record of consistently strongly influencing positive portfolio performance.</li><li>Proactive in managing credit risk in assigned industries/sectors by monitoring existing holdings and portfolio weightings.</li><li>Apply strong communication skills, both written and verbal, with the ability to influence portfolio managers to consider and implement recommendations into portfolios without prompting or suggestion from others.</li><li>Mentor and guide more junior analysts and/or summer interns within fixed income by providing training and support as needed.</li><li>Model Thrivent's leadership competencies Model the Way, Rally the Team, and Deliver Outcomes.</li><li>Support and/or develop an environment in which Thrivent employees and colleagues are focused on continuous improvement, exceptional employee engagement, and an unwavering commitment to our clients. Shape and/or support a culture that represents the Thrivent purpose, promise and values, ensuring that Thrivent's trust and reputation remain strong with its clients.</li></ul>Job QualificationsRequired:<ul><li>Minimum 6 years relevant investment professional experience;</li><li>Relevant experience may include full-time investment professional work or academic investment work equivalent, or internships, preferably focused on credit risk evaluation, plus:</li><ul><li>Master's degree in finance, business, economics or related area, or</li><li>CFA designation.</li></ul><li>Alternative requirements: Bachelor's degree in finance, accounting or related discipline plus a minimum of 15 years of successful investment professional experience.</li><li>Expert understanding or broad knowledge of specific investment asset class or Fixed Income.</li><li>Ability and eagerness to work collaboratively in a team environment.</li><li>Self-motivation and drive to establish process for impact on results.</li><li>High level of organization and attention to detail.</li><li>Strong problem-solving skills to develop solutions that are unique to solve complex problems</li><li>Strong communication skills across team and direct leadership.</li><li>Strong technical skills, including proficient skills in using Microsoft Office suite, Bloomberg and Aladdin, or related systems.</li></ul>Preferred:<ul><li>Master of Business Administration, Finance or other advanced degree in relevant field, with money management or applied securities experience, and CFA designation.</li><li>Ability to prioritize work against enterprise, division, and product strategies; can effectively communicate rationale and impact for prioritization choice.</li></ul>Additional Information<ul><li>This position requires you to work on-site in Minneapolis, MN a minimum of three days a week.</li></ul>Pay TransparencyThrivent's long-term growth depends on attracting, rewarding, and retaining people who are committed to helping others thrive with purpose. We accomplish this by offering a wide variety of market competitive compensation programs to attract, reward, and retain top talent. The applicable salary or hourly wage range for this full-time role is $177,984.00 - $240,803.00 per year, which factors in various geographic regions. The base pay actually offered will be determined by a variety of factors including, but not limited to, location, relevant experience, skills, and knowledge, business needs, market demand, and other factors Thrivent deems important.Thrivent is unique in our commitment to helping people to be wise with money and live balanced and generous lives. That extends to our benefits. The following benefits may be offered: various bonuses (including, for example, annual or long-term incentives); medical, dental, and vision insurance; health savings account; flexible spending account; 401k; pension; life and accidental death and dismemberment insurance; disability insurance; supplemental protection insurance; 20 days of Paid Time Off each year; Sick and Safe Time; 10 paid company holidays; Volunteer Time Off; paid parental leave; EAP; well-being benefits, and other employee benefits. Eligibility for receipt of these benefits is subject to the applicable plan/policy documents. Thrivent's plans/policies are subject to change at any time at Thrivent's discretion.Thrivent provides Equal Employment Opportunity (EEO) without regard to race, religion, color, sex, gender identity, sexual orientation, pregnancy, national origin, age, disability, marital status, citizenship status, military or veteran status, genetic information, or any other status protected by applicable local, state, or federal law. This policy applies to all employees and job applicants.Thrivent is committed to providing reasonable accommodation to individuals with disabilities. If you need a reasonable accommodation, please let us know by sending an email to human.resources@thrivent.com or call 800-847-4836 and request Human Resources.</div>

<div><h2>Senior Research Analyst II, High-Yield</h2>We exist to help people achieve financial clarity. At Thrivent, we believe money is a tool, not a goal. Driven by a higher purpose at our core, we are committed to providing financial advice, investments, insurance, banking and generosity programs to help people make the most of all they've been given. At our core, we are a membership-owned fraternal organization, as well as a holistic financial services organization, dedicated to serving the unique needs of our clients. We focus on their goals and priorities, guiding them toward financial choices that will help them live the life they want todayand tomorrow.Job SummaryThe Senior Research Analyst II, High-Yield is the second level research analyst responsible for independent research covering a particular industry. This role analyzes and recommends the purchase and sale of public high yield corporate bonds and related securities that contribute to incremental outperformance within the analyst's assigned industries. Analysts at the Senior II level conduct research analyses on specific organizations, securities, financial products, and the overall economic environment with minimal director oversight. In addition, the Senior II Research Analyst monitors existing investments, manages credit risk, makes industry recommendations, and maintains relative weighting and relative value recommendations within the high yield credit market. This level analyst consistently positively impacts portfolios. Success in this role requires working well in a team environment, effectively prioritizing individual workflow and market-driven demands, and generating consistent, superior performance. The Research function is responsible for conducting research analyses on specific organizations, securities, financial products, and the overall economic environment.Job Responsibilities and Duties<ul><li>Perform independent, fundamental credit analysis on issuers within assigned industries. Has a strong understanding of assigned credits/industries. Has the ability to take on new and/or additional coverage.</li><li>Analyze company financial statements from a bondholder's perspective to develop an opinion of the company's operational strengths, weaknesses, and directional outlook.</li><li>Develop and maintain financial models to evaluate credit worthiness.</li><li>Prepare detailed credit reports and provide relative value opinions, which lead to portfolio recommendations.</li><li>Play an active role in managing credit risk in assigned industries/sectors by monitoring existing holdings and portfolio weightings.</li><li>Make recommendations on issuer/industry/trade that are regularly implemented by portfolio managers.</li><li>Demonstrates a track record of consistently strong performance that positively impacts portfolio performance.</li><li>Apply strong communication skills, both written and verbal, with the ability to influence portfolio managers to consider and implement recommendations into portfolios.</li><li>Mentor and guide more junior analysts and/or summer interns within credit research by providing training and support as needed.</li><li>Model Thrivent's leadership competencies Model the Way, Rally the Team, and Deliver Outcomes.</li><li>Support and/or develop an environment in which Thrivent employees and colleagues are focused on continuous improvement, exceptional employee engagement, and an unwavering commitment to our clients. Shape and/or support a culture that represents the Thrivent purpose, promise and values, ensuring that Thrivent's trust and reputation remain strong with its clients.</li></ul>Job QualificationsRequired:<ul><li>Minimum of 4 years, likely more, relevant investment professional experience;</li><li>Relevant experience may include full-time investment professional work or academic investment work equivalent or internships, preferably focused on credit risk evaluation, plus:</li><ul><li>Master's degree in finance, business, economics or related area, or</li><li>Progress toward CFA designation.</li></ul><li>Alternative requirements: Bachelor's degree in finance, accounting or related discipline plus a minimum of 10 years of successful investment professional experience.</li><li>Strong working knowledge of accounting, finance, government/tax policy or related market.</li><li>Strong written, verbal, and interpersonal communications skills.</li><li>Demonstrated ability to disseminate information concisely and confidently.</li><li>Ability and eagerness to work collaboratively in a team environment.</li><li>Ability to work independently and offer thought leadership to more junior research analysts or portfolio managers.</li><li>High level of organization and attention to detail.</li><li>Strong technical skills, including advanced skills in using Microsoft Office suite, Bloomberg and Aladdin or related systems.</li></ul>Preferred:<ul><li>5 - 7 years of investment research analyst experience, plus</li><li>Master of Business Administration, Finance or other advanced degree in relevant field, with money management or applied securities experience, or attainment of CFA designation.</li></ul>Additional Information<ul><li>This position requires you to work on-site in Minneapolis, MN a minimum of three days a week.</li></ul>Pay TransparencyThrivent's long-term growth depends on attracting, rewarding, and retaining people who are committed to helping others thrive with purpose. We accomplish this by offering a wide variety of market competitive compensation programs to attract, reward, and retain top talent. The applicable salary or hourly wage range for this full-time role is $153,750.00 - $208,015.00 per year, which factors in various geographic regions. The base pay actually offered will be determined by a variety of factors including, but not limited to, location, relevant experience, skills, and knowledge, business needs, market demand, and other factors Thrivent deems important.Thrivent is unique in our commitment to helping people to be wise with money and live balanced and generous lives. That extends to our benefits. The following benefits may be offered: various bonuses (including, for example, annual or long-term incentives); medical, dental, and vision insurance; health savings account; flexible spending account; 401k; pension; life and accidental death and dismemberment insurance; disability insurance; supplemental protection insurance; 20 days of Paid Time Off each year; Sick and Safe Time; 10 paid company holidays; Volunteer Time Off; paid parental leave; EAP; well-being benefits, and other employee benefits. Eligibility for receipt of these benefits is subject to the applicable plan/policy documents. Thrivent's plans/policies are subject to change at any time at Thrivent's discretion.Thrivent provides Equal Employment Opportunity (EEO) without regard to race, religion, color, sex, gender identity, sexual orientation, pregnancy, national origin, age, disability, marital status, citizenship status, military or veteran status, genetic information, or any other status protected by applicable local, state, or federal law. This policy applies to all employees and job applicants. Thrivent is committed to providing reasonable accommodation to individuals with disabilities. If you need a reasonable accommodation, please let us know by sending an email to human.resources@thrivent.com or call 800-847-4836 and request Human Resources.</div>

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

Thrivent Interview Questions

Thrivent Interview Guides