10 OneMain Holdings SQL Interview Questions (Updated 2024)
At OneMain Holdings, SQL is often for analyzing consumer patterns in the financial services sector and managing loan distribution data across various branches. That's the reason behind why OneMain Holdings asks SQL questions in interviews for Data Analytics, Data Science, and Data Engineering jobs.
So, to help you study, here’s 10 OneMain Holdings SQL interview questions – can you answer each one?
10 OneMain Holdings SQL Interview Questions
SQL Question 1: Identify The Whale Users
OneMain Holdings is primarily a financial services holding company. Suppose the company wishes to identify its 'whale users' for their financial products. A 'whale user' in this context is a customer who has taken multiple loans in the past year and has an excellent repayment record. Your task is to write a SQL query that retrieves these power users.
In particular, you need to identify all the users who have taken more than 5 loans in the past year and have made all their repayments on time.
Example Input:
| loan_id | user_id | loan_issue_date | loan_amount |
|---|---|---|---|
| 1001 | 425 | 01/04/2021 | 6000 |
| 2035 | 619 | 02/10/2021 | 4000 |
| 4067 | 425 | 03/15/2021 | 5000 |
| 3921 | 223 | 07/28/2021 | 3500 |
| 5402 | 619 | 09/30/2021 | 3000 |
| 7182 | 425 | 11/29/2021 | 7500 |
Example Input:
| repayment_id | loan_id | repayment_date | repayment_amount |
|---|---|---|---|
| 7001 | 1001 | 05/04/2021 | 2000 |
| 8582 | 2035 | 06/10/2021 | 2000 |
| 5124 | 4067 | 09/15/2021 | 2500 |
| 6583 | 3921 | 11/28/2021 | 1750 |
| 3796 | 5402 | 03/30/2022 | 1500 |
| 7073 | 7182 | 03/29/2022 | 3750 |
Answer:
The SQL query joins the and tables on the loan id. It then filters for loans taken out in the last year where repayments were made within 30 days of the loan issue date. It groups the results by the user id and selects only those users who took more than 5 such loans in the past year. These are the 'whale users' for OneMain Holdings.
To practice a related customer analytics question on DataLemur's free interactive coding environment, try this Microsoft Teams Power User SQL Interview Question:
SQL Question 2: Employee Salaries Higher Than Their Manager
Assume you had a table of OneMain Holdings employee salaries. Write a SQL query to find all employees who earn more than their direct manager.
OneMain Holdings Example Input:
| employee_id | name | salary | department_id | manager_id |
|---|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 | |
| 2 | Daniel Rodriguez | 2230 | 1 | 10 |
| 3 | Olivia Smith | 8000 | 1 | 8 |
| 4 | Noah Johnson | 6800 | 2 | 8 |
| 5 | Sophia Martinez | 1750 | 1 | 10 |
| 8 | William Davis | 7000 | 2 | NULL |
| 10 | James Anderson | 4000 | 1 | NULL |
Example Output:
| employee_id | employee_name |
|---|---|
| 3 | Olivia Smith |
This is the output because Olivia Smith earns $8,000, surpassing her manager, William Davis who earns 7,800.
Try this problem directly within the browser on DataLemur:
Answer:
First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.
If the code above is confusing, you can find a detailed solution here: Employees Earning More Than Their Boss.
SQL Question 3: Why should you normalize your database?
Database normalization has several benefits:
-
Reduces Redundancy: Normalization can minimize redundancy by breaking down a larger, general table into smaller, more granular tables. This often reduces the amount of data that needs to be accessed for particular queries, since some duplicated columns can be removed.
-
Improves Data Integrity: Normalization can help to ensure the integrity of the data by minimizing the risk of data inconsistencies and errors. By establishing clear relationships between the tables via primary and foreign keys, and enforcing these constraints, you can have more reliable records and relationships stored in your DB.
-
Improves Performance: Normalization can improve the performance of the database by reducing the amount of data that needs to be stored and accessed in a single table. This results in faster query times and better overall performance.
SQL Question 4: Calculating Monthly Loan Default Rates
OneMain Holdings is a company that offers personal loans. One important piece of information that they might be interested in tracking is the monthly default rates for their loans across different regions.
Assume a SQL table is available with the following data:
Example Input:
| loan_id | borrower_id | region_id | issue_date | loan_amount | defaulted |
|---|---|---|---|---|---|
| 50001 | 123 | 1 | 06/10/2022 | $2000 | True |
| 69852 | 265 | 2 | 06/22/2022 | $1500 | False |
| 45689 | 362 | 1 | 07/15/2022 | $3000 | True |
| 85279 | 192 | 3 | 07/21/2022 | $4000 | False |
| 98731 | 981 | 2 | 08/05/2022 | $2500 | True |
The column is a Boolean with 'True' indicating that the loan has defaulted, and 'False' meaning it hasn't.
Write a SQL query to calculate the default rate for each month (the total amount of loans defaulted / total amount of loans issued), for each region.
Example Output:
| month | region | default_rate |
|---|---|---|
| 6 | 1 | 1 |
| 6 | 2 | 0 |
| 7 | 1 | 1 |
| 7 | 3 | 0 |
| 8 | 2 | 1 |
Answer:
Here is the PostgreSQL query:
This query first creates a CTE that groups the loans by month and region. For each group, it calculates the total amount of defaulted loans and the total amount of loans issued.
Then, it calculates the default rate by dividing by , making sure to cast to decimal to allow for floating point division.
The result is the default rate for each month and region.
To solve a related window function SQL problem on DataLemur's free interactive SQL code editor, try this Google SQL Interview Question:
Check out OneMain's career page and see where you might fit best!
SQL Question 5: Can you provide a comparison of cross join and natural join?
Cross joins and natural joins are two types of JOIN operations in SQL that are used to combine data from multiple tables. A cross join creates a new table by combining each row from the first table with every row from the second table, and is also known as a cartesian join. On the other hand, a natural join combines rows from two or more tables based on their common columns, forming a new table. One key difference between these types of JOINs is that cross joins do not require common columns between the tables being joined, while natural joins do.
Here's an example of a cross join:
If you have 20 products and 10 colors, that's 200 rows right there!
Here's a natural join example using two tables, OneMain Holdings employees and OneMain Holdings managers:
This natural join returns all rows from OneMain Holdings employees where there is no matching row in managers based on the column.
SQL Question 6: Analyzing Loan Repayments Over Time
OneMain Holdings is a company that offers personal loans. The company would like to analyze repayment patterns of its customers. An essential question is - How does the total repayment amount change monthly? What proportion of the total loan have customers repaid on average every month?
You have been tasked with analyzing two tables and .
Example Input:
| loan_id | customer_id | issue_date | loan_amount |
|---|---|---|---|
| 1 | 1001 | 01/01/2022 | 10000 |
| 2 | 1002 | 02/15/2022 | 15000 |
| 3 | 1003 | 03/20/2022 | 20000 |
| 4 | 1004 | 04/25/2022 | 25000 |
| 5 | 1001 | 05/01/2022 | 30000 |
Example Input:
| repayment_id | loan_id | repayment_date | repayment_amount |
|---|---|---|---|
| 1 | 1 | 01/31/2022 | 1000 |
| 2 | 1 | 02/28/2022 | 1000 |
| 3 | 2 | 03/15/2022 | 1500 |
| 4 | 2 | 04/15/2022 | 1500 |
| 5 | 3 | 05/15/2022 | 2000 |
Note: Each loan can have multiple repayments. Each repayment is linked to a loan via the .
Write a SQL query that would output the total repayment monthly from all customers, and the average proportion of loan repaid monthly (total repayment amount over loan amount).
Expected Output:
| month_year | total_repayment | average_repayment_ratio |
|---|---|---|
| January, 2022 | 1000 | 0.1 |
| February, 2022 | 2000 | 0.1 |
| March, 2022 | 1500 | 0.10 |
| April, 2022 | 1500 | 0.075 |
| May, 2022 | 2000 | 0.05 |
Answer:
This query first joins the and tables based on . Then, we group the results by month and year, calculating the sum of repayments and the average repayment ratio (repayment_amount divided by loan_amount) for each month. Lastly, the result is returned in ascending order of the month and year.
SQL Question 7: How is a foreign key different from a primary key in a database?
To explain the difference between a primary key and foreign key, let's start with an example OneMain Holdings sales database:
:
+------------+------------+------------+------------+ | order_id | product_id | customer_id| quantity | +------------+------------+------------+------------+ | 1 | 303 | 1 | 2 | | 2 | 404 | 1 | 1 | | 3 | 505 | 2 | 3 | | 4 | 303 | 3 | 1 | +------------+------------+------------+------------+
In this table, could be a primary key. It is unique for each row in the table and cannot contain null values.
and could both be foreign keys. They reference the primary keys of other tables, such as a Products table and a Customers table, respectively. This establishes a relationship between the table and the other tables, such that each row in the sales database corresponds to a specific product and a specific customer.
SQL Question 8: Customer Loan Details Filtering
OneMain Holdings, Inc. is a company providing personal loan products. They're interested in filtering their customer records to gain insights about customers who have taken a loan of more than $5000, are from the state of New York, and have a good payment history (no missed payments).
You are asked to write a query that will filter down the user_loan records based on these multiple boolean conditions.
Example Input:
| customer_id | first_name | last_name | state |
|---|---|---|---|
| 001 | Micheal | Andersen | New York |
| 002 | Sarah | Johnson | California |
| 003 | Robert | Gonzalez | Texas |
| 004 | Jessica | Smith | New York |
| 005 | James | Brown | New York |
Example Input:
| loan_id | customer_id | loan_date | loan_amount |
|---|---|---|---|
| 616 | 001 | 06/08/2022 | 7000 |
| 781 | 002 | 06/10/2022 | 2000 |
| 533 | 003 | 06/18/2022 | 2500 |
| 635 | 004 | 07/26/2022 | 5500 |
| 451 | 005 | 07/05/2022 | 8000 |
Example Input:
| customer_id | loan_id | missed_payments |
|---|---|---|
| 001 | 616 | 0 |
| 002 | 781 | 1 |
| 003 | 533 | 2 |
| 004 | 635 | 0 |
| 005 | 451 | 3 |
Answer:
This query will join the , , and tables on their and , applying the given conditions on the , , and . The result will be a list of customers from New York who have taken a loan of more than $5000 and have never missed a payment.
SQL Question 9: Filtering Customer Records
OneMain Holdings is a company specializing in personal finance services and happens to have customers across the United States. The customer database contains customer details with information like customer ID, name, city, state, and the date they became a customer. For a marketing campaign, the company wants to focus its efforts on customers from specific states. This campaign is primarily focused on all the customers whose states start with the letter 'M', 'N', or 'O'.
You are provided with a snapshot of the Customer table. Write a SQL query to fetch all customers from states starting with 'M', 'N', or 'O'. You should return the customer_id, name, city, state, and customer_since in your results.
Example Input
| customer_id | name | city | state | customer_since |
|---|---|---|---|---|
| 1001 | John Doe | Houston | Texas | 2018-06-01 |
| 1002 | Jane Smith | New York City | New York | 2019-03-15 |
| 1003 | Mary Johnson | Orlando | Florida | 2020-06-20 |
| 1004 | James Brown | Albuquerque | New Mexico | 2017-07-07 |
| 1005 | Emily Davis | Baltimore | Maryland | 2018-08-08 |
Answer:
This SQL query filters the Customer records table based on the condition provided in the WHERE clause. It checks the 'state' field to see if it starts with 'M', 'N', or 'O'. The result is a list of customers who are in the states starting with 'M', 'N', or 'O'. The keyword is used to match text string patterns when combined with wildcard characters in SQL. The percentage sign is used to check the pattern that starts with 'M', 'N', or 'O'.
SQL Question 10: What's the difference between relational and non-relational databases?
While both types of databases are used to store data (obviously), there's some key differences in how they store and organize data.
Relational databases try to represent the world into neat little tables, with rows and columns. Non-relational (NoSQL) databases use a variety of data models to represent data, including document, key-value, columnar, and graph storage formats.
While the exact types of NoSQL databases is beyond the scope of a Data Analyst and Data Scientist SQL interview at OneMain Holdings, it's good to know that companies generally choose to use NoSQL databases:
- when dealing with unstructured or semi-structured data
- when the database needs to be scaled horizontally easily
- when the data is non-relational (like storing social network data which makes more sense in a graph format)
How To Prepare for the OneMain Holdings SQL Interview
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the OneMain Holdings SQL interview is to solve as many practice SQL interview questions as you can!
Beyond just solving the above OneMain Holdings SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Google, Facebook, Microsoft and Amazon.
Each SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and best of all, there is an online SQL coding environment so you can instantly run your SQL query and have it graded.
To prep for the OneMain Holdings SQL interview it is also wise to practice SQL questions from other mortgage & loan companies like:
However, if your SQL skills are weak, forget about jumping right into solving questions – strengthen your SQL foundations with this free SQL tutorial.
This tutorial covers SQL concepts such as sorting data with ORDER BY and Self-Joins – both of these come up frequently during SQL interviews at OneMain Holdings.
OneMain Holdings Data Science Interview Tips
What Do OneMain Holdings Data Science Interviews Cover?
In addition to SQL interview questions, the other question categories to prepare for the OneMain Holdings Data Science Interview are:
- Probability & Statistics Questions
- Coding Questions in Python or R
- Product Data Science Interview Questions
- Machine Learning Questions
- Resume-Based Behavioral Questions
How To Prepare for OneMain Holdings Data Science Interviews?
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