9 D.E. Shaw SQL Interview Questions (Updated 2024)
At D.E. Shaw, SQL is used to analyze financial data patterns, such as identifying trends in stock prices, trading volumes, and market sentiment, as well as to optimize algorithms for risk management, including portfolio optimization and stress testing. Because of this, D.E. Shaw frequently asks SQL problems during interviews for Data Analyst, Data Science, and BI jobs.
To help you practice for the D.E. Shaw SQL interview, here's 9 D.E. Shaw SQL interview questions in this blog.
9 D.E. Shaw SQL Interview Questions
SQL Question 1: Identify High Trading Volume Customers
D.E. Shaw is a multinational investment management firm that is heavily reliant on computation and algorithmic trading. One way to identify important (or "whale") users for such a company could be to look for individuals or institutions that frequently execute large number of trades, as such users are potential sources of substantial fee revenues.
Your task is to write a SQL query that identifies users who had made more than 50 trades in the last 30 days.
Example Input:
| trade_id | user_id | trade_date | asset_id |
|---|---|---|---|
| 3245 | 21 | 06/08/2022 | A101 |
| 2478 | 43 | 06/10/2022 | B205 |
| 2965 | 21 | 06/10/2022 | C304 |
| 1398 | 33 | 07/15/2022 | A101 |
| 6780 | 43 | 07/20/2022 | B205 |
Answer:
This query first filters the trades table to only include trades made in the last 30 days. It then groups the data by user_id, and counts the number of trades each user made. The HAVING clause is used to filter out users with 50 or fewer trades, meaning we only keep the users with more than 50 trades. We then sort users in descending order of number of trades to make the most active traders easy to identify.
To practice a similar VIP customer analysis question on DataLemur's free online SQL code editor, try this Microsoft Azure Cloud SQL Interview Question:
SQL Question 2: 2nd Largest Salary
Suppose there was a table of D.E. Shaw employee salary data. Write a SQL query to find the 2nd highest salary amongst all the .
D.E. Shaw Example Input:
| employee_id | salary |
|---|---|
| 1 | 2500 |
| 2 | 800 |
| 3 | 1000 |
| 4 | 1200 |
Example Output:
| second_highest_salary |
|---|
| 1200 |
You can solve this problem directly within the browser on DataLemur:
Answer:
You can find a detailed solution here: 2nd Highest Salary.
SQL Question 3: 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 stress about knowing which DBMS supports what exact commands since the interviewers at D.E. Shaw should be lenient!).
Here's a PostgreSQL example of using EXCEPT to find all of D.E. Shaw's Facebook video ads with more than 10k views that aren't also being run on YouTube:
If you want to retain duplicates, you can use the EXCEPT ALL operator instead of EXCEPT. The EXCEPT ALL operator will return all rows, including duplicates.
SQL Question 4: Calculate Monthly Average Ratings per Product
D.E. Shaw is interested in analyzing the performance of its investment products over time. They want to understand the trends in how users are rating their products on a monthly basis to gain insights for product development and client satisfaction.
Assume that you have a table named with the following schema:
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 101 | 456 | 2022-03-01 | 10987 | 3 |
| 102 | 237 | 2022-03-15 | 10987 | 4 |
| 103 | 654 | 2022-03-20 | 12345 | 5 |
| 104 | 654 | 2022-04-01 | 12345 | 4 |
| 105 | 237 | 2022-04-15 | 12345 | 5 |
| 106 | 456 | 2022-05-01 | 10987 | 3 |
| 107 | 654 | 2022-05-15 | 10987 | 2 |
You are required to write a SQL query to calculate the monthly average rating for each product. Your result should include the month, the product id, and the average stars for that product in the given month.
Expected Output:
| month | product_id | avg_stars |
|---|---|---|
| 3 | 10987 | 3.50 |
| 3 | 12345 | 5.00 |
| 4 | 12345 | 4.50 |
| 5 | 10987 | 2.50 |
Answer:
You can achieve this by using the function along with the window function in PostgreSQL. Here is the SQL query:
The solution uses to extract the month from . It also uses within the window function to calculate the average stars for each product within each month separately. The is then used to consolidate these averages calculations by month and product_id, and the results are then ordered to display the trends chronologically.
For more window function practice, solve this Uber SQL problem on DataLemur's interactive coding environment:
SQL Question 5: What's the difference between and ?
The operator merges the output of two or more statements into a single result set. It ignores duplicated rows, and makes sure each row in the result set is unique.
For a concrete example, say you were a Data Analyst at D.E. Shaw working on a Marketing Analytics project. If you needed to get the combined result set of both D.E. Shaw's Google and Facebook ads you could execute this SQL query:
The operator works in a similar way to combine data from multiple statements, but it differs from the operator when it comes to handling duplicate rows. Whereas filters out duplicates (so if the same ad_name is run on both Facebook and Google, it only shows up once), outputs duplicate rows.
SQL Question 6: D.E. Shaw - Track Stock Transactions
D.E. Shaw is a global investment and technology development firm. In such a company, it's important to track stock transactions. Imagine they want to model a database that captures the stocks bought and sold by their brokers.
Design a database for them. You'll need a table for brokers (), another table for stocks (), and a transaction table () to capture the many-to-many relationship between brokers and stocks.
Your task is to come up with these three tables, and model the relationships between them. Also, each stock will have a and , and each broker will have a , , and .
Please simulate data for five different stocks, three brokers, and at least five transactions.
Table:
| broker_id | first_name | last_name |
|---|---|---|
| 1 | John | Doe |
| 2 | Jane | Smith |
| 3 | Jim | Brown |
Table:
| ticker_symbol | company_name |
|---|---|
| AAPL | Apple Inc. |
| TSLA | Tesla, Inc. |
| AMZN | Amazon.com, Inc. |
| GOOGL | Google LLC |
| MSFT | Microsoft Corporation |
Table:
| transaction_id | broker_id | ticker_symbol | transaction_date | quantity | transaction_type |
|---|---|---|---|---|---|
| 1 | 1 | AAPL | 06/01/2022 00:00:00 | 10 | BUY |
| 2 | 2 | TSLA | 06/05/2022 00:00:00 | 5 | SELL |
| 3 | 1 | AMZN | 06/15/2022 00:00:00 | 20 | BUY |
| 4 | 3 | GOOGL | 07/10/2022 00:00:00 | 15 | SELL |
| 5 | 2 | MSFT | 07/20/2022 00:00:00 | 30 | BUY |
Now, you are asked to write a query that returns a report of the total number of shares bought and sold for each stock by each broker.
Answer:
This SQL query will join three tables on their relationships and use CASE statement to distinguish between 'BUY' and 'SELL' transactions. It then aggregates the quantities of shares bought or sold for each stock for each broker.
SQL Question 7: What are the different types of database indexes?
A database index is a data structure that provides a quick lookup of data in a column or columns of a table.
There are several types of indexes that can be used in a database:
- Primary index: a unique identifier is used to access the row directly.
- Unique index: used to enforce the uniqueness of the indexed columns in a table.
- Composite index: created on multiple columns of a table, is used to speed up the search process for multiple columns
- Clustered index: determines the physical order of the data in a table
SQL Question 8: Filtering Customer Information Based on Multiple Conditions
D.E. Shaw & Co. is interested in examining the trading patterns of its customers. In particular, they would like to identify customers who have traded more than $1,000,000 in a single stock, are flagged as High Net Worth individuals and live in a specific state.
For this SQL interview question, suppose you are given a table and a table. The table contains the customer's id (), their name (), whether they are flagged as a High Net Worth individual (), and their state of residence ().
The table contains the id of the customer who executed the trade (), the id of the traded stock (), the traded volume (), and the trading date ().
Sample Input:
| customer_id | customer_name | high_net_worth | state |
|---|---|---|---|
| 101 | Adam Jones | YES | NY |
| 102 | Betty Smith | NO | AZ |
| 103 | Chris Johnson | YES | TX |
| 104 | David Brown | YES | NY |
Sample Input:
| trade_id | customer_id | stock_id | trade_volume | trade_date |
|---|---|---|---|---|
| 201 | 101 | 501 | 2000000 | 2022-01-01 |
| 202 | 102 | 502 | 500000 | 2022-01-02 |
| 203 | 104 | 503 | 1500000 | 2022-01-03 |
| 204 | 103 | 504 | 2000000 | 2022-01-02 |
The SQL query problem for this case: Write a PostgreSQL query that selects the of customers who have traded more than $1,000,000 in a single stock, are flagged as High Net Worth individuals and live in NY.
Answer:
In the above query, a JOIN operation is performed between and tables on the field. Then the WHERE clause filters out the customers who meet the given conditions: is 'YES', is 'NY' and is larger than 1,000,000. The query then returns the names of these customers.
SQL Question 9: Calculate Maximum Trade Volumes by Product
As an analyst at D.E. Shaw, you are tasked with monitoring the trading activity for the various financial products the company deals with. Write an SQL query to determine the product type which has the highest sum of traded volumes each month.
Assuming you are given the following table:
Example Input:
| trade_id | trader_id | trade_date | product_id | volume |
|---|---|---|---|---|
| 101 | 343 | 06/03/2022 | 7809 | 500 |
| 205 | 654 | 06/05/2022 | 6723 | 300 |
| 309 | 124 | 06/23/2022 | 7809 | 200 |
| 410 | 789 | 07/01/2022 | 6723 | 900 |
| 512 | 345 | 07/23/2022 | 7809 | 100 |
Your result should return the following format:
Example Output:
| mth | product_id | max_volume |
|---|---|---|
| 6 | 7809 | 700 |
| 7 | 6723 | 900 |
Answer:
Here is the PostgreSQL query to find the requested information:
This query groups data by month and product id, it then sums the trade volume for each group. The results are ordered by month and volume, visualizing the product with maximum trade volume for each month.
Preparing For The D.E. Shaw SQL Interview
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the D.E. Shaw SQL interview is to solve as many practice SQL interview questions as you can! Beyond just solving the above D.E. Shaw SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.
Each DataLemur SQL question has hints to guide you, full answers and most importantly, there's an online SQL code editor so you can right in the browser run your SQL query answer and have it checked.
To prep for the D.E. Shaw SQL interview you can also be a great idea to solve SQL questions from other finance companies like:
Get the inside scoop on D.E. Shaw's latest developments and innovations in finance and technology!
However, if your SQL foundations are weak, don't worry about diving straight into solving questions – improve your SQL foundations with this interactive SQL tutorial.
This tutorial covers things like grouping by multiple columns and cleaning text data – both of which show up frequently in D.E. Shaw SQL interviews.
D.E. Shaw Data Science Interview Tips
What Do D.E. Shaw Data Science Interviews Cover?
Beyond writing SQL queries, the other types of questions to practice for the D.E. Shaw Data Science Interview include:
- Statistics and Probability Questions
- Python Pandas or R Coding Questions
- Analytics and Product-Metrics Questions
- ML Modelling Questions
- Behavioral & Resume-Based Questions
How To Prepare for D.E. Shaw Data Science Interviews?
To prepare for the D.E. Shaw Data Science interview make sure you have a firm understanding of the company's culture and values – this will be important for acing the behavioral interview. For the technical Data Science interviews, prepare by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from FAANG tech companies
- A Refresher covering Python, SQL & ML
- Amazing Reviews (1000+ 5-star reviews on Amazon)