9 American National SQL Interview Questions (Updated 2024)

Data Analysts & Data Scientists at American National use SQL to extract insights from large datasets, such as policyholder behavior and claims history, for risk evaluation. It is also used for designing and maintaining the databases for their insurance and financial solutions, including optimizing database performance and ensuring data quality, which is why American National asks interviewees SQL interview questions.

To help prep you for the American National SQL interview, here’s 9 American National Group SQL interview questions in this article.

9 American National Group SQL Interview Questions

SQL Question 1: Average Insurance Claim Per Month Per State

Consider you have access to American National's claim data. The company wants to understand the average claim amount made by customers on a monthly basis grouped by each state. This should help them in their risk assessment where rates are generally linked to historical claim data. Your task is to write a SQL query that will calculate the average claim amount per state for each month.

Let's consider we have the following table:

Example Input:

Expected Output:

Answer:

In PostgreSQL, you can use the function to get the month from a date. To calculate the average claim amount per state for each month, you can use the function grouped by and .

Here's the SQL query:

This SQL Query will give you the average claim amount for each state on a monthly basis. The result is sorted first by month, and then by state, to make it easier to read.

For more window function practice, try this Uber SQL problem within DataLemur's online SQL coding environment:

SQL Question 2: Top 3 Department Salaries

Assume you had a table of American National employee salary data. Write a SQL query to find the top 3 highest paid employees within each department.

American National Example Input:

Example Input:

Example Output:

Check your SQL query for this interview question interactively on DataLemur:

Answer:

We use the DENSE_RANK() window function to generate unique ranks for each employee's salary within their department, with higher salaries receiving lower ranks. Then, we wrap this up in a CTE and filter the employees with a ranking of 3 or lower.

If the solution above is hard to understand, you can find a step-by-step solution here: Top 3 Department Salaries.

SQL Question 3: What does the SQL keyword do?

The clause in SQL allows you to select records that are unique, eliminating duplicates.

For example, if you had a table of American National employees, and wanted to see what are all the unique job titles that currently worked at the company, you could write the following query:

SQL Question 4: Filter Customer Records

The American National company maintains a database of their customers. They periodically need to filter these records for marketing targeting. They are planning a campaign that targets the customers who have policies expiring soon, living in the states of Texas or California, and are in the age range of 30-50. Write a SQL query to filter these customers out of the customer's database.

The table structure is as follows:

Example Input:

Please note that the date is in format 'YYYY-MM-DD'.

Answer:

The above SQL query first filters for customers who live either 'Texas' or 'California' utilizing the 'IN' command. Then it checks for customers whose ages are between 30 and 50 using the clause. Finally, it checks if the policy_expiration_date is within the next three months from the current date using the clause. This will return all the customers that satisfy all these conditions.

SQL Question 5: When would you use the / commands in SQL?

The / operator is used to remove to return all rows from the first SELECT statement that are not returned by the second SELECT statement.

Note that is available in PostgreSQL and SQL Server, while MINUS is available in MySQL and Oracle (but don't worry about knowing which DBMS supports which exact commands since American National interviewers aren't trying to trip you up on memorizing SQL syntax).

For a tangible example of in PostgreSQL, suppose you were doing an HR Analytics project for American National, and had access to American National's contractors and employees data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables.

You could use operator to find all contractors who never were a employee using this query:

SQL Question 6: Calculate the Average Policy Premium per Customer for Each Policy Type

As an insurance firm, American National needs to continually analyze their data for useful insights. One such insight they may be interested in is the average policy premium per customer for each type of policy they offer. Calculate this average.

Example Input:

Example Output:

Answer:

The above SQL query groups the policies based on the type, and then calculates the average premium amount for each group, returning the average premium amount per customer for each type of policy.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating aggregated metrics per group or this Amazon Average Review Ratings Question which is similar for calculating averages for each group.

SQL Question 7: Can you explain the distinction between a correlated and a non-correlated sub-query?

A correlated sub-query is a sub-query that depends on the outer query and cannot be executed separately. It uses the outer query to filter or transform data by referencing a column from it, and the outer query uses the results of the inner query. In contrast, a non-correlated sub-query is independent of the outer query and can be executed on its own. It does not reference any columns from the outer query and is used to retrieve additional data needed by the outer query.

Here is an example of a correlated sub-query:

This query selects the and total sales of all American National customers in the sales table whose are greater than the average of their own customer group. The sub-query in this case is correlated with the outer query, as it references the column from the outer query ().

Here is an example of a non-correlated sub-query:

The sub-query in this case is non-correlated, as it does not reference any columns from the outer query.

Performance-wise, correlated sub-queries are generally slower to execute, as they have to be re-evaluated for each row of the outer query, while non-correlated sub-queries are faster, as they only have to be executed once.

SQL Question 8: Filtering customer records in American National

You are a data analyst at American National. You have been tasked with filtering down the company's customer records to identify customers from Texas (TX) and whose email is a gmail address. The emails in the data are formatted as .

You are using PostgreSQL.

Sample input is provided in the table :

Example Input:

The desired output is a table containing only the customer_id, full_name and email of the matched customers from TX having Gmail accounts.

Example output:

Example Output:

Answer:

The given query uses the keyword in SQL to match patterns - in this case, it checks if the field ends with '@gmail.com'. This query also includes a condition to ensure that the is 'TX', as specified in the question. The fields that are needed for the query's output are listed in the statement. The , , and fields will be included in the output where the state is 'TX' and email ends with '@gmail.com'.

SQL Question 9: Calculate Average Monthly Premiums for Different Policy Types

Given a database of policyholders, their policy types, the initial amount of their policies and the change in policy amount every month, can you write an SQL query to calculate the average monthly premiums for each policy type, rounded to the nearest whole number? Assume the monthly policy amount can be calculated by the formula .

Example Input:

Example Input:

You are required to write an SQL query that calculates the average monthly premium per policy type for the first year (considering the change in policy amount every month).

Answer:

This query first constructs a table with all monthly amounts for each policy for the first year using a cartersian product, considering the change_per_month into account for each ensuing month. After that, it calculates the average monthly premiums for each policy type, rounded to the nearest whole number. Finally, it selects and orders the data by policy type.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating the top values within a category or this Facebook Average Review Ratings Question which is similar for calculating an average and grouping by a category.

Preparing For The American National SQL Interview

The best way to prepare for a American National SQL interview is to practice, practice, practice. In addition to solving the above American National SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Netflix, Google, and Amazon.

Each SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and most importantly, there's an interactive SQL code editor so you can right online code up your query and have it checked.

To prep for the American National SQL interview you can also be useful to solve SQL questions from other insurance companies like:

• American National SQL questions
• Digital Realty Trust SQL questions
• Country Financial SQL questions
• Public Storage SQL questions

Stay informed about American National's latest news and developments, shaping the future of insurance and financial services!

But if your SQL foundations are weak, forget about diving straight into solving questions – refresh your SQL knowledge with this free SQL tutorial.

This tutorial covers SQL topics like joins and math functions like ROUND()/CEIL() – both of which come up often in SQL interviews at American National.

American National Group Data Science Interview Tips

What Do American National Data Science Interviews Cover?

Besides SQL interview questions, the other types of questions covered in the American National Data Science Interview are:

• Probability & Stats Questions
• Python or R Coding Questions
• Data Case Study Questions
• Machine Learning Questions
• Behavioral Questions centered on American National company values

How To Prepare for American National Data Science Interviews?

To prepare for American National Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions taken from Google, Microsoft & tech startups
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Don't ignore the behavioral interview – prepare for that with this guide on acing behavioral interviews.