logo

10 OneMain Holdings SQL Interview Questions (Updated 2024)

Updated on

June 30, 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?

OneMain Holdings SQL Interview Questions

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_iduser_idloan_issue_dateloan_amount
100142501/04/20216000
203561902/10/20214000
406742503/15/20215000
392122307/28/20213500
540261909/30/20213000
718242511/29/20217500
Example Input:
repayment_idloan_idrepayment_daterepayment_amount
7001100105/04/20212000
8582203506/10/20212000
5124406709/15/20212500
6583392111/28/20211750
3796540203/30/20221500
7073718203/29/20223750

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: Microsoft SQL Interview Question: Teams Super User

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_idnamesalarydepartment_idmanager_id
1Emma Thompson38001
2Daniel Rodriguez2230110
3Olivia Smith800018
4Noah Johnson680028
5Sophia Martinez1750110
8William Davis70002NULL
10James Anderson40001NULL

Example Output:

employee_idemployee_name
3Olivia 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:

Employees Earning More Than Their Manager

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.

OneMain Holdings SQL Interview Questions

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_idborrower_idregion_idissue_dateloan_amountdefaulted
50001123106/10/2022$2000True
69852265206/22/2022$1500False
45689362107/15/2022$3000True
85279192307/21/2022$4000False
98731981208/05/2022$2500True

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:
monthregiondefault_rate
611
620
711
730
821

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: 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_idcustomer_idissue_dateloan_amount
1100101/01/202210000
2100202/15/202215000
3100303/20/202220000
4100404/25/202225000
5100105/01/202230000
Example Input:
repayment_idloan_idrepayment_daterepayment_amount
1101/31/20221000
2102/28/20221000
3203/15/20221500
4204/15/20221500
5305/15/20222000

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_yeartotal_repaymentaverage_repayment_ratio
January, 202210000.1
February, 202220000.1
March, 202215000.10
April, 202215000.075
May, 202220000.05

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_idfirst_namelast_namestate
001MichealAndersenNew York
002SarahJohnsonCalifornia
003RobertGonzalezTexas
004JessicaSmithNew York
005JamesBrownNew York
Example Input:
loan_idcustomer_idloan_dateloan_amount
61600106/08/20227000
78100206/10/20222000
53300306/18/20222500
63500407/26/20225500
45100507/05/20228000
Example Input:
customer_idloan_idmissed_payments
0016160
0027811
0035332
0046350
0054513

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_idnamecitystatecustomer_since
1001John DoeHoustonTexas2018-06-01
1002Jane SmithNew York CityNew York2019-03-15
1003Mary JohnsonOrlandoFlorida2020-06-20
1004James BrownAlbuquerqueNew Mexico2017-07-07
1005Emily DavisBaltimoreMaryland2018-08-08

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. DataLemur Questions

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.

Interactive 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:

OneMain Holdings Data Scientist

How To Prepare for OneMain Holdings Data Science Interviews?

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

  • 201 interview questions taken from Facebook, Google, & Amazon
  • a refresher on SQL, Product-Sense & ML
  • over 1000+ reviews on Amazon & 4.5-star rating

Ace the Data Science Interview by Nick Singh Kevin Huo