11 Merck SQL Interview Questions (Updated 2024)
Merck employees write SQL queries to analyze clinical trial data, helping them assess the effectiveness of new drugs and treatments. They also use SQL to manage patient data for personalized medicine research, allowing them to tailor treatments to individual patient needs, that is the reason why Merck includes SQL coding problems during interviews for Data Analytics, Data Science, and Data Engineering roles.
So, to help you prepare, here’s 11 Merck SQL interview questions – how many can you solve?
11 Merck SQL Interview Questions
SQL Question 1: Calculate the Average Medicine Satisfaction Score by Year and Quarter
Merck is a global healthcare company that, among other things, produces a variety of medicines. For a given dataset that includes customer reviews of Merck's medicines, write a SQL query to calculate the average customer satisfaction scores for each medicine, grouped by year and quarter. The satisfaction score is a rating on a scale of 1-5 stars and the results should be ordered by year, quarter and average satisfaction in descending order.
Assume we have a table that stores all the customer reviews of various medicines. Each review has an unique , the of the reviewer, the of the review, the of the medicine and the rating.
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 271 | 246 | 2021-01-25 | 25701 | 4 |
| 334 | 982 | 2021-03-16 | 25701 | 5 |
| 183 | 456 | 2021-02-18 | 25701 | 2 |
| 998 | 812 | 2021-06-17 | 35464 | 4 |
| 578 | 734 | 2021-04-02 | 35464 | 3 |
| 293 | 560 | 2021-05-28 | 35464 | 4 |
| 660 | 124 | 2021-08-04 | 35464 | 3 |
| 531 | 221 | 2021-11-29 | 25701 | 4 |
Example Output:
| year | quarter | product_id | avg_stars |
|---|---|---|---|
| 2021 | 4 | 25701 | 4 |
| 2021 | 3 | 35464 | 3.5 |
| 2021 | 2 | 35464 | 3.5 |
| 2021 | 1 | 25701 | 3.67 |
Answer:
This SQL query extracts the year and the quarter from the field with function for each review. Then, it groups the rows by , and and calculates the average satisfaction for each group. The results are ordered in descending order of year, quarter and average satisfaction score. The function is used to round the average rating to two decimal places.
Pro Tip: Window functions are a popular SQL interview topic, so practice all the window function problems on DataLemur
Dive into Merck's media and news releases to learn about their latest advancements and contributions to the pharmaceutical industry! Keeping up with Merck can help you appreciate how they are working to improve health outcomes through innovative solutions.
SQL Question 2: 2nd Largest Salary
Suppose you had a table of Merck employee salary data. Write a SQL query to find the 2nd highest salary amongst all the .
Merck Example Input:
| employee_id | salary |
|---|---|
| 1 | 2500 |
| 2 | 800 |
| 3 | 1000 |
| 4 | 1200 |
Example Output:
| second_highest_salary |
|---|
| 1200 |
Code your solution to this interview question interactively on DataLemur:
Answer:
You can find a step-by-step solution with hints here: 2nd Highest Salary.
SQL Question 3: What are the similarities and differences between a clustered index and non-clustered index?
Here's an example of a clustered index on the column of a table of Merck payments table:
This creates a clustered index on the column, which will determine the physical order of the data rows in the table.
Here is an example of a non-clustered index on the column of the same table:
This will create a non-clustered index on the column, which will not affect the physical order of the data rows in the table.
In terms of query performance, a clustered index is usually faster for searches that return a large number of records, while a non-clustered index is faster for searches that return a small number of records. However, updates to a clustered index are slower, as they require the data rows to be physically rearranged, while updates to a non-clustered index are faster, as they only require the index data structure to be updated.
SQL Question 4: Analyze Medication Sales Data
As a data analyst at Merck, your task is to write a query that filters down the medication sales data to only show records for 'Category X' medications sold in the 'USA' and 'Canada' between 2020 and 2022. Ignore transactions with quantities less than 100 units.
Example Input:
| sales_id | medication_id | category | sales_date | country | quantity_units |
|---|---|---|---|---|---|
| 7812 | 908 | Category X | 06/10/2020 | USA | 105 |
| 9536 | 524 | Category Y | 06/08/2021 | Canada | 90 |
| 4821 | 258 | Category X | 06/18/2022 | USA | 300 |
| 6921 | 651 | Category Z | 07/26/2020 | USA | 250 |
| 5342 | 908 | Category X | 07/05/2020 | Canada | 80 |
| 9945 | 256 | Category X | 08/30/2022 | USA | 200 |
Example Output:
| sales_id | medication_id | category | sales_date | country | quantity_units |
|---|---|---|---|---|---|
| 7812 | 908 | Category X | 06/10/2020 | USA | 105 |
| 4821 | 258 | Category X | 06/18/2022 | USA | 300 |
| 9945 | 256 | Category X | 08/30/2022 | USA | 200 |
Answer:
In this query, we are fetching all the columns from the table by applying multiple condition checks. We are filtering the records where is 'Category X', the is either 'USA' or 'Canada', lies between 2020 and 2022, and the is greater than or equal to 100.
SQL Question 5: What's the difference between a one-to-one vs. a one-to-many relationship between two entities? Give examples.
In database schema design, a one-to-one relationship is when each entity is associated with only one instance of the other. For instance, a US citizen's relationship with their social-security number (SSN) is one-to-one because each citizen can only have one SSN, and each SSN belongs to one person.
A one-to-many relationship, on the other hand, is when one entity can be associated with multiple instances of the other entity. An example of this is the relationship between a person and their email addresses - one person can have multiple email addresses, but each email address only belongs to one person.
SQL Question 6: Average Number of Clinical Trials per Investigator
As an analyst at Merck, one of the leading pharmaceutical companies, you are tasked with finding the average number of clinical trials each investigator has overseen over the past year. Investigators may oversee more than one trial at a time.
Use the following sample tables for your analysis:
Example Input:
| investigator_id | name |
|---|---|
| 1 | Dr. Smith |
| 2 | Dr. Johnson |
| 3 | Dr. Williams |
Example Input:
| trial_id | investigator_id | start_date | end_date |
|---|---|---|---|
| 101 | 1 | 01/01/2021 | 06/01/2021 |
| 102 | 2 | 02/01/2021 | 07/01/2021 |
| 103 | 1 | 03/01/2021 | 08/01/2021 |
| 104 | 3 | 02/01/2021 | 07/01/2021 |
| 105 | 1 | 05/01/2021 | 10/01/2021 |
| 106 | 2 | 07/01/2021 | 12/01/2021 |
| 107 | 3 | 03/01/2021 | 08/01/2021 |
| 108 | 2 | 09/01/2021 | 02/01/2022 |
Answer:
This query first groups the clinical trials by investigator and counts the number of trials each investigator has overseen in the past year. It then joins this subquery with the investigators table and calculates the average number of trials.
To practice a very similar question try this interactive LinkedIn Duplicate Job Listings Question which is similar for handling multiple entries by a single identity or this Twitter Histogram of Tweets Question which is similar for dealing with frequency count per user.
SQL Question 7: How do you select records without duplicates from a table?
The clause is used to remove all duplicate records from a query.
For example, if you had a table of open jobs Merck was hiring for, and wanted to see what are all the unique job titles that were currently available at the company, you could write the following query:
SQL Question 8: Analyze Click-Through Rate for Merck's Digital Pharmaceutical Ads
Merck & Co., a multinational pharmaceutical company, runs various digital ads promoting their products to customers. Your job is to analyze the click-through rates (CTR) of these digital ads. CTR is calculated as the ratio of users who click on the ad to the number of total users who view the ad.
Use the following tables for your analysis:
Example Input:
| impression_id | user_id | impression_date | ad_id | product_id |
|---|---|---|---|---|
| 3241 | 789 | 06/08/2022 00:00:00 | 1234 | 9981 |
| 4502 | 479 | 06/10/2022 00:00:00 | 3465 | 9982 |
| 8713 | 200 | 06/18/2022 00:00:00 | 1234 | 9981 |
| 1124 | 320 | 07/26/2022 00:00:00 | 5678 | 9983 |
| 6791 | 987 | 07/05/2022 00:00:00 | 1234 | 9981 |
Example Input:
| click_id | user_id | click_date | ad_id | product_id |
|---|---|---|---|---|
| 4321 | 789 | 06/08/2022 00:00:00 | 1234 | 9981 |
| 5422 | 890 | 06/10/2022 00:00:00 | 3465 | 9982 |
| 7891 | 200 | 06/18/2022 00:00:00 | 1234 | 9981 |
| 7865 | 320 | 07/26/2022 00:00:00 | 5678 | 9983 |
You'll need to write a SQL query to calculate the click-through rate for each ad, monthly.
Answer:
This query firstly groups the impressions and clicks by month and ad_id. Then it counts the number of unique impressions and unique clicks for each month and ad. Subsequently, it calculates the click-through rate by dividing the number of clicks by the number of impressions. The final result is ordered by month and in descending order to identify the ads with the highest click-through rates in each month.
To practice another question about calculating rates, solve this SQL interview question from TikTok within DataLemur's online SQL coding environment:
SQL Question 9: Find the Maximum Sold Pharmaceuticals each Month
Merck is a large pharmaceutical company. For any business dealing in products like pharmaceuticals, it's very useful to know the performance of their various products sales. Suppose you are given a sales table named for Merck pharmaceuticals. The table has the following columns:
Example Input:
| sale_id | product_id | sale_date | quantity |
|---|---|---|---|
| 7891 | 963 | 08/10/2021 | 255 |
| 5693 | 982 | 08/12/2021 | 196 |
| 6375 | 996 | 08/15/2021 | 300 |
| 6425 | 963 | 09/05/2021 | 279 |
| 6525 | 982 | 09/20/2021 | 310 |
| 7925 | 996 | 10/25/2021 | 245 |
The task is to write a PostgreSQL query that retrieves the pharmaceutical product which sold the most in each month.
Answer:
In the query above, we use to isolate the month from the . We then the month and to arrange our data. In each of these groups, we find the max quantity, effectively finding the product that sold the most in each month. The final result will provide a clear view of sales by product and month.
SQL Question 10: What do foreign key's do?
A foreign key is a column or group of columns in a table that refers to the primary key in another table. The foreign key constraint helps maintain referential integrity between the two tables.
Let's examine employee data from Merck's HR database:
:
| employee_id | first_name | last_name | manager_id |
|---|---|---|---|
| 1 | Aubrey | Graham | 3 |
| 2 | Marshal | Mathers | 3 |
| 3 | Dwayne | Carter | 4 |
| 4 | Shawn | Carter |
In this table, serves as the primary key and functions as a foreign key because it links to the of the employee's manager. This establishes a relationship between Merck employees and their managers, allowing for easy querying to find an employee's manager or see which employees report to a specific manager.
The table may also have multiple foreign keys that reference primary keys in other tables. For example, and foreign keys could be used to connect each employee to their respective department and location.
SQL Question 11: Fetching Specific Drug Records from Merck Database
Merck, a leading pharmaceutical company, maintains a comprehensive product database. The database encompasses diverse drugs, each with a unique name and ID. The company is interested in fetching records of a specific drug category starting with 'Anti-' from their database.
A part of their database table 'drugs' is given below:
Example Input:
| drug_id | drug_name | category | price | quantity |
|---|---|---|---|---|
| 1001 | Antipyretic | Anti-inflammatory | 500 | 850 |
| 1002 | Antihistamine | Anti-allergic | 750 | 200 |
| 1003 | Atenolol | Beta blocker | 300 | 600 |
| 1004 | Atorvastatin | Statin | 400 | 700 |
| 1005 | Antibiotic | Anti-bacterial | 450 | 500 |
| 1006 | Anti-cough | Anti-tussive | 350 | 300 |
The SQL query is expected to return all those records where the drug category starts with "Anti-".
Answer:
To solve this problem, we could use the keyword of SQL. The SQL query would look something like this:
This SQL statement selects all records from the table where the field starts with "Anti-".
Expected Output:
| drug_id | drug_name | category | price | quantity |
|---|---|---|---|---|
| 1001 | Antipyretic | Anti-inflammatory | 500 | 850 |
| 1002 | Antihistamine | Anti-allergic | 750 | 200 |
| 1005 | Antibiotic | Anti-bacterial | 450 | 500 |
| 1006 | Anti-cough | Anti-tussive | 350 | 300 |
As per the output, only the records where the 'category' field starts with "Anti-" have been selected.
Merck SQL Interview Tips
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews. Beyond just solving the above Merck SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Netflix, Google, and Amazon.
Each interview question has hints to guide you, detailed solutions and crucially, there is an interactive SQL code editor so you can easily right in the browser your SQL query and have it graded.
To prep for the Merck SQL interview it is also useful to solve SQL problems from other healthcare and pharmaceutical companies like:
But if your SQL foundations are weak, don't worry about jumping right into solving questions – improve your SQL foundations with this interactive SQL tutorial.
This tutorial covers topics including how window functions work and sorting data with ORDER BY – both of these show up frequently during SQL interviews at Merck.
Merck Data Science Interview Tips
What Do Merck Data Science Interviews Cover?
In addition to SQL interview questions, the other types of problems tested in the Merck Data Science Interview include:
- Statistics and AB Testing Questions
- Python Pandas or R Coding Questions
- Product Analytics Questions
- Machine Learning Questions
- Behavioral Questions centered on Merck cultural values
How To Prepare for Merck Data Science Interviews?
To prepare for Merck Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions taken from FAANG (FB, Apple, Amazon, Netflix, Google)
- a crash course on SQL, Product-Sense & ML
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Also focus on the behavioral interview – prepare for that using this guide on acing behavioral interviews.