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How to Prepare for a SQL Take-Home

The concepts to study, how to practice, and what to include.

You found a dream analytics engineering role on LinkedIn with a company whose mission you are extremely passionate about.

You submitted your resume and heard back from the recruiter. You passed the initial phone screening and even talked to the hiring manager. You can already picture yourself working on the data team of this company!

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Top 21 Data Science Take-home Challenges with Instructions (Updated for 2024)

Data science take-home challenges are a common type of assessment used in data science interviews , and they sometimes take the place of the technical screen.

Take-home challenges are essentially mini data science projects . You have a business case study problem and a dataset, and then you must perform analysis, build a model, write working code, and make product recommendations.

These challenges take 3 to 8 hours to complete, and they’re used to screen candidates for open data science and machine learning roles. One of the biggest mistakes that candidates make is failing to understand expectations and spending too much time on a solution that doesn’t meet the interviewer’s criteria.

To help you prepare, we’ve compiled the top data science take-home challenges in these categories:

Data Analytics Take-Home Challenges

Machine learning take-home challenges, sql take-home challenges.

• Product Case Take-Home Challenges

Tips for Passing Data Science Take-Homes

A data science take-home isn’t just an opportunity to display strong technical skills. These challenges provide a chance to show how well you gather input, communicate your findings, and approach solving technical challenges on the job.

If you’re looking for help, you can follow these tips for passing data science take-homes:

Understand expectations

It’s tempting to jump into a take-home challenge without correctly understanding expectations. However, a short email to the recruiter can provide direction and ensure you head down the right track. In your email, include the following:

• Your timeline for completing the assignment
• Ask for any general guidelines on grading
• Ask for feedback after submitting your assignment.

State your assumptions and limitations

What if you only use a naive imputation model to fill in missing values instead of an advanced technique? State it. Write it in a comment. Do something where they understand your limitations to the amount of time you spend on the assignment.

Write up everything that you think needs to be known to your grader. Hiring managers forgot how long it took to write code and build models. They’re managers, and typically they don’t write code.

Do the modeling basics

Here’s a general checklist that will probably take you at least three hours:

• Data cleaning
• Minimal feature selection
• Impute missing values
• Create a classification pipeline
• Try training with a couple of sci-kit learn classifiers
• Tune hyperparameters with grid-search

Your implementation will reach the general minimal baseline of what they’re expecting. Dependent on how long you work on feature selection, it could go plus or minus an extra two to three hours.

Make your take-home challenge readable

Take-homes are an opportunity to show how you communicate technical concepts. Use a framework for organizing your ideas, like the Cookiecutter Data Science Framework . This framework will make your analysis easier to follow, enable interviewers to learn about your process and domain knowledge, and feel more confident in your conclusions.

Although formatting your work will take more time, it’ll show that you can communicate data analysis succinctly and make your work accessible.

Write tests and comments

Readability is as important as the efficiency of your code, and if you write nice comment blocks on each function, it will help communicate how your code should function and why you re-factored it the way you did. Follow the general Python conventions to make sure you’re solid.

Summarize your process in 500 words or less

The reviewer will only spend 10 minutes or less reviewing your challenge, so give them a reason to dig deeper. If you can succinctly describe your work and make it easy to understand, you’ll be much more likely to pass and move on.

Analytics take-home challenges are most common in data analyst roles. These challenges commonly provide a dataset and require you to perform exploratory data analysis. In some cases, guiding questions will be asked to help direct your analysis, and often, you’ll be required to make product or business recommendations based on your research.

1. Stripe Analytics Take-Home

• Overview: Perform EDA on a product data set from Stripe and make product recommendations.
• Time Required: 6 hours
• Skills Tested: EDA, analytics, product sense
• Deliverable: Short presentation

The Stripe take-home tests product and data sense, as well as your understanding of growth marketing. For the assignment, you’re provided data on core Stripe products and user segment data and are required to create a presentation on your findings.

Some guiding questions ask about product/user segment performance, making general forecasts for performance, and any potential product issues.

2. Instacart Data Analyst Challenge

• Overview: Perform exploratory data analysis of Instacart orders.
• Time Required: 3 hours
• Skills Tested: Analytics, product sense, data storytelling.
• Deliverable: Create a deck or document that conveys your analyses about Instacart products.

In the past, Instacart provided this take-home test to data analysts. This assignment is focused on exploratory data analysis and includes a dataset relating to Instacart orders, order location, customer ratings, and any issues reported for a set of demands.

This assignment is brief, requiring about 3 hours to complete, and the deliverable is a deck, slides, or a document that conveys your analyses of the business.

3. Masterclass Analytics Assignment

• Overview: Perform analysis of traffic to the Gordon Ramsey Masterclass homepage.
• Time Required: 3.5 hours
• Skills Tested: Analytics, growth marketing, user behavior analysis.
• Deliverable: Compile your analyses and code in a Jupyter Notebook.

Masterclass’s analytics take-home analyzes traffic to its Gordon Ramsey course marketing page. You’re provided with 30 days of user activity data, which includes relevant information like location, event, marketing channel, and traffic source.

With your analysis, Masterclass asks for data analysts who are both “reactive and proactive” and who can pull insights about user behavior. For example, you could investigate behavior by channel, comparing paid traffic to organic social traffic. Or you could determine the effectiveness of remarketing efforts.

4. Twitter Data Analytics Assignment

• Overview: Evaluate an A/B test and complete a dice probability case study.
• Skills Tested: A/B testing, probability, and statistics, EDA
• Deliverable: A notebook describing your methodology and code.

Twitter’s data analyst take-home assignment comes in two parts and focuses primarily on statistics and A/B testing. The first question is a probability question, asking you to calculate the probability for different scenarios in the game of craps.

However, the question is a bit more challenging because, in the scenario, one of the dice is “unfair.” The second question focuses on A/B testing and tests your ability to pull analytics metrics. Specifically, you’re tasked to measure the success of a product A/B test using the data provided.

5. Amazon Take-Home Assignment

• Overview: Complete a probability and data analytics case study regarding inventory.
• Time Required: 6 Hours
• Skills Tested: Statistics, Python, time-series analysis
• Deliverable : Create a brief describing your methodology, Python code, and responses to provided questions.

This Amazon data science take-home focuses on probability and time-series analysis and tests your Python coding ability. This assignment is a case study question that provides time-series data about inventory shortages. Your goal with the work is to determine the volume of lost sales due to inventory shortages.

Machine learning take-home assignments generally fall into two categories: 1) build a model based on provided data or 2) evaluate or improve a model. These take-home tasks typically ask you to provide a Jupyter Notebook with working code; however, you’ll also need to synthesize your methodology.

Some top FAANG machine learning take-home tasks include:

6. Opendoor Machine Learning Take-Home

• Overview: Build a simple prediction model for housing prices and complete two Python coding problems.
• Skills Tested: Modeling, machine learning, Python coding
• Deliverable: Submit a Jupyter Notebook with a working code.

This assignment is a three-part take-home; however, it’s recommended that you spend 3 hours on it.

The first part asks you to take a small real estate transaction dataset and build a simple model to predict housing prices. The key here is explaining your choices. Describe the methodology you use, model performance, and next steps.

In Parts 2 and 3, two shorter problems test applied Python programming skills.

7. Capgemini Machine Learning Task

• Overview: Build and evaluate models to predict national retail store sales for each store and department.
• Skills Tested: Modeling, statistics, Python
• Deliverable: Prepare a 20- to 30-minute presentation for a general technical audience.

Capgemini’s machine learning challenge presents you with a dataset of retail sales. However, the sales data is very seasonal and holiday based. Like many machine learning challenges, the presentation is more important than the model, and it should include the following:

• Presentation of insights/conclusions
• Relevant descriptive statistics and visualizations
• The mathematical principles behind your model
• Model diagnostics and interpretation

8. Airbnb Algorithms Take-Home

• Overview: Train is a recommender model that can predict which listings a specific user is likely to book​.
• Time Required: 72 hours
• Skills Tested: Machine learning, recommendation engines, algorithms
• Deliverable: Please submit one document and provide code and a write-up.

This assignment is an in-depth, three-day model-building take-home with minimal direction. For this recommendation engine problem, Airbnb suggests formulating it as a ranking problem or a top-K recommendation problem.

The key to this challenge is your model-building process. Where do you start (e.g., a baseline model)? And what are the steps you use to tune the model?

9. DoorDash Machine Learning Coding Challenge

• Overview: Build​ ​a​ ​machine​ ​learning​ model​ ​​for​ a ​prediction task​ and write an​​ application​ ​ to​ make​ ​predictions using​ ​that​ ​model.
• Time Required: 5.5 hours
• Skills Tested: Machine learning, Python, regression analysis
• Deliverable: A short write-up explaining your model, code for the model, and code that outputs a .tsv file for the application.

This assessment is a two-part machine learning challenge. The first is a classic modeling case study where you build a model to predict total delivery duration in seconds.

DoorDash’s take-home is meant to test your model tuning and evaluation skills, define why you used the model, how you evaluated performance, and any information of note about your approach.

It would also help if you made recommendations based on your model to reduce delivery time. You must create an app that uses the model to predict each delivery in the JSON file and writes out predictions to a new ​tab-separated file.

To learn how to solve a DoorDash Analytics Case Study , see our step-by-step guide.

10. NielsenIQ Machine Learning Take-Home

• Overview: Build a classification model for text data.
• Skills Tested: Machine learning, Python, classification, NLP
• Deliverable: Create a presentation as well as a Jupyter Notebook with code.

This take-home challenge tests your Natural Language Processing and classification skills. You have two types of text strings split into two files. Using this data, you’ll create a classification model that accurately labels the data. You’re free to use any machine learning techniques or metrics that you would like.

SQL coding challenges typically include a set of SQL problems, and you must write queries for a given dataset. These challenges are common for data science and analytics roles and may also assess your product sense and analytics domain knowledge.

Here are some top data science SQL take-home tasks:

11. Uber SQL Take-Home Assignment

• Overview: Given the below subset of Uber’s schema, write executable SQL queries to answer the questions below.
• Skills Tested: Analytics, SQL, Python, A/B testing
• Deliverable: Write a single query for each question.

This assessment is a three-part SQL challenge that tests your applied SQL skills and ability to draw insights from data and evaluate A/B tests. The three-part challenge includes:

• Part 1: write SQL queries to answer sample questions like calculating the difference between actual and predicted ETA.
• Part 2: A new driver app has been developed at Uber. You must define the primary metrics for the app, as well as design a test to evaluate the redesigned app’s performance.
• Part 3: The last step asks you to determine which factors are best at predicting whether a newly signed-up driver will start to drive and offer suggestions to operationalize those insights to help Uber.

12. NextDoor SQL Coding Take-Home

• Overview: Complete simple SQL queries of a given dataset, design tables for a KPI dashboard, and write queries for the dashboard.
• Skills Tested: SQL, database design, data engineering
• Deliverable: Sample SQL queries and table designs.

This assessment is a classic SQL take-home in that you must develop whiteboard queries based on provided table schema.

However, there’s an additional step, which includes database design and data engineering skills. The data engineering section asks you to design tables for a KPI dashboard and, ultimately, to write queries to populate those tables.

13. McKinsey SQL & EDA Take-Home

• Overview: Write SQL queries for a bike-sharing program dataset and answer specific questions about the data.
• Skills Tested: Analytics and SQL
• Deliverable: Create a brief presentation, including visualizations, for your analysis.

This challenge combines your SQL skills and exploratory data analysis. You’re provided a dataset of a bike-sharing program in Washington, DC.

The first part asks you questions that would require intermediate to advanced SQL queries to analyze popular routes. The second part asks you to identify imbalances in where bikes are picked up or dropped off.

In addition, a product metrics question requires you to propose top metrics to monitor the program’s health.

14. Qventus Whiteboard SQL and Storytelling Take-Home

• Overview: Query a dataset and answer questions. Evaluate if a machine learning model has a real-world business impact.
• Skills Tested: SQL, analytics, business case
• Deliverable: Work on a SQL code, a discussion of limitations, and an outline for an analytics story about the ML model.

This take-home from the AI-driven healthcare company Qventus has been given to data analysts and focuses on practical SQL coding skills and data visualization ability.

The first problem is a classic SQL case study; you’re provided with a dataset and required to answer questions like “What percentage of patient visits are still admitted or not discharged yet from the hospital?”

The second part asks you to evaluate a model developed to predict patient surges at hospitals and describe through a data story and visualizations if the model has the intended impact.

15. DraftKings Data Analyst Challenge

• Overview: This three-part challenge covers data sense, applied SQL knowledge, and programming knowledge.
• Skills Tested: SQL, Python, analytics
• Deliverable: A short document covering a simple data analysis case study, raw SQL queries, and Python code for automation tasks.

This assessment is a direct data analyst SQL challenge. The first part asks you to analyze a data visualization and describe what you see. This question is open to interpretation.

The following steps require you to query a sports analytics database to pull metrics about soccer athletes. Finally, the last problem is a scripting challenge, and you’re required to write Python code to automate sample data analytics tasks.

Product Case Study Take-Home Challenges

Product case study take-homes typically incorporate a few skills, including data analytics, product analysis, and SQL. Most of these challenges provide a business or product case and then ask you to make recommendations about the product to improve performance, reduce costs, or increase market share.

The most popular product case study take-homes for data scientists include:

16. Airbnb Growth Take-Home

• Overview: Analyze the provided data and make product recommendations to help increase bookings in Rio de Janeiro.
• Skills Tested: Analytics, EDA, growth marketing, data visualization
• Deliverable: S​ummarize your recommendations in response to the questions above in a Jupyter Notebook intended for the Head of Product and VP of Operations (who is not technical).

This take-home is a classic product case study. You have booking data for Rio de Janeiro, and you must define metrics for analyzing matching performance and make recommendations to help increase the number of bookings.

This take-home includes grading criteria, which can help direct your work. Assignments are judged on the following:

• Analytical approach and clarity of visualizations
• Your data sense and decision-making, as well as the reproducibility of the analysis
• Strength of your recommendations
• Your ability to communicate insights in your presentation
• Your ability to follow directions

17. Affirm Merchant Analysis Take-Home

• Overview: Analyze a provided dataset and recommend improving the product or business.
• Skills Tested: Product sense, EDA, analytics, SQL
• Deliverable: Submit SQL code to answer questions and document discussing recommendations.

Affirm’s product take-home assignment includes a dataset related to the company’s checkout process. You perform EDA on that dataset and answer specific queries like “Calculate conversion through the funnel by day.”

However, the real challenge comes in step two; then, you must make product recommendations to improve performance and then choose one of those recommendations for experimentation. You then give specifics about how you would test the product.

18. Lyft Drive Churn Case Study

• Overview: Analyze a Lyft dataset for driver churn and make recommendations to reduce churn.
• Time Required: 1 hour
• Skills Tested: Business case, pandas, R
• Deliverable: Submit answers to provided questions, along with the applicable code.

Lyft’s take-home is short and used to thin the candidate pool in place of a technical screen.

You write responses to questions like, How would you define driver churn? How would you calculate churn based on your answer? These questions are high-level and ask you to propose technical solutions. The key here is communicating your responses concisely and clearly.

19. Grubhub Growth Marketing Take-Home

• Overview: Analyze the data and recommend which states Grubhub should expand.
• Skills Tested: Marketing analytics, business case, growth marketing
• Deliverable: Present your recommendations and discuss any limitations or assumptions you made

This take-home challenge provides you with a bare-bones dataset, including orders, visits to Grubhub’s site, and revenue.

Because the dataset is so limited, you’ll be required to “make assumptions and list them in your response.” Ultimately, you’ll recommend which states to target for expansion.

20. City Year Client Case Study

• Overview: Use data from the presented case to make recommendations on fundraising strategy for City Year.
• Skills Tested: Business case, probability
• Deliverable: Present your recommendation in a format appropriate for a non-technical executive.

This business case take-home is a probability case study. It will require you to take a simulated dataset of response rates and average donations and, using that data, determine how City Year should prioritize its fundraising strategy, e.g., corporate donors vs. individuals.

This question is based on probability, as you’ll be able to calculate which method would generate the most fundraising impact for the company.

21. Uber Data Science Takehome Challenge

• Overview: How would you measure the success of the redesigned Uber app?
• Skills Tested: Analytics and Product Metrics
• Deliverable: Identify 2-3 secondary metrics that, in conjunction with the primary success metric, will provide a more comprehensive picture of the app’s performance.

This take-home involves a new version of the app that offers more comprehensive information on earnings, and driver ratings, and introduces a unified platform for communication between Uber and its partners. Your task is to propose and define the primary success metric for the redesigned app. Justify your choice.

Video: Data Science Take-Home Tips

In this Interview Query video, Jay provides an overview of how to pass data science take-home challenges. Specifically, the video offers tips for approaching a take-home, what you should include in your submission, and questions you should ask before you get started. See his data science take-home advice here:

SQL Interview Questions: 3 Tech Screening Exercises For Data Analysts (in 2022)

• Tomi Mester
• May 31, 2022

I’ve been part of many job interviews – on both sides of the table. The most fun, but also the most feared, part of the process is the technical screening. In this article, I’ll show you three SQL test exercises that, in my experience, are quite typical in data analyst job interviews — as of 2022. (And hey, these are “sample” SQL interview questions but they are heavily based on reality!)

Before the tasks – What can you expect in an SQL technical screening?

There are two common ways an SQL tech screening can be done.

The simpler but less common way is that you get a computer, a data set, and a task. While you are solving the task, the interviewers are listening and asking questions. A little trial-and-error is totally fine, as long as you can come up with the correct solution in a reasonable amount of time.

The other, more difficult (and by the way much more common) way is the whiteboard interview. In this case, you don’t get a computer. You have to solve the task and sketch up the code on a whiteboard. This means that you won’t get feedback (at least not from a computer) on whether you made a logical or a syntax error in your code. Of course, you can still solve the tasks by thinking iteratively. You can crack the different SQL problems one by one… But you have to be very confident with your SQL skills.

Additionally, usually, you have to solve the tasks on the fly. Maybe you will get 3-5 minutes of thinking time but that’s the maximum you can expect.

I know, this sounds stressful . And it is. But don’t worry, there is some good news, as well. Because companies know that this is a high-stress interview type, compared to the real-life challenges, you will get relatively simpler tasks. (See the difficulty level below!)

SQL tech assessments in 2022

There are several types of SQL tech assessments. The one that I described above (and for that, I’ll provide a few exercises below) is the most common one. When people say “SQL tech screening,” they usually refer to that. To be more precise, I like to call it “in-person SQL screening.”

But, in fact, there are four different types of SQL assessments:

• In-person SQL screening. The one that we discussed so far (and will discuss in the rest of the article).
• SQL quiz questions. For example: “What is a primary key?” Or “List the different types of JOIN s!” That’s a stupid type of SQL tech assessment — as it focuses on theory and not on practice. Still, some companies… you know.
• Take-home SQL assignment. You get a more complex task and you’ll have to write multiple SQL queries to solve it. The upside is that can work from home, as you get the task and the dataset by email. You get these on a workday you choose, and you’ll have ~12 hours to solve it and send the solution back (SQL queries and a short presentation). I like this assessment type, as it creates a less stressful environment for the applicant.
• Automated SQL screening. With the rise of remote work, automated SQL screening becomes more common. It’s usually a one-hour process with a few simpler SQL tasks – that you can solve from home via a browser. This interview type is not very personal, but I like it as it’s less stressful and more flexible (e.g. you can skip tasks and go back later).

When someone asks you to do an “SQL tech screening,” either of the above can come up. Still, the most common is the in-person SQL screening. So let’s see a few examples of that!

Test yourself!

Here are three SQL interview questions that are really close to what I actually got or gave on data analyst/scientist job interviews!

Try to solve all of them as if they were whiteboard interviews!

In the second half of the article, I’ll show you the solutions, too!

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SQL Interview Question #1

Let’s say you have two SQL tables: authors and books . The authors dataset has 1M+ rows. Here’s a small sample, the first six rows:

The books dataset also has 1M+ rows and here’s the first six:

Create an SQL query that shows the TOP 3 authors who sold the most books in total!

(Note: Back in the days, I got almost this exact SQL interview question for a data scientist position at a very well-known Swedish IT company.)

SQL Interview Question #2

You work for a startup that makes an online presentation software. You have an event log that records every time a user inserted an image into a presentation. (One user can insert multiple images.) The event_log SQL table looks like this:

…and it has over one billion rows.

Note: If the event_date_time column’s format doesn’t look familiar, google “epoch timestamp”!

Write an SQL query to find out how many users inserted more than 1000 but less than 2000 images in their presentations!

(Note: I personally created and used this interview question to test data analysts when I was freelancing and my clients needed help in their hiring process.)

SQL Interview Question #3

You have two SQL tables!

The first table is called employees and it contains the employee names, the unique employee ids, and the department names of a company. Sample:

The second SQL table is called salaries . It holds the same employee names and the same employee ids – and the salaries for each employee. Sample:

The company has 546 employees, so both tables have 546 rows.

Print every department where the average salary per employee is lower than $500!

(Note: I created this test question based on a real SQL interview question that I heard from a friend, who applied at one of the biggest social media companies (name starts with ‘F.’ ;))

Solution of SQL Interview Question #1

The solution code is:

And here is a short explanation:

1. First you have to initiate the JOIN . I joined the two tables by using:

2. After that, I used a SUM() function with a GROUP BY clause. This means that in the SELECT statement I had to replace the * with the author_name and sold_copies columns. (It’s not mandatory to indicate from which table you are selecting the columns, but it’s worth it. That’s why I used authors .author_name and books .sold_copies .)

3. Eventually, I ORDER ed the results in DESC ending order. (Just for my convenience, I also renamed the sum column to sold_sum using the AS sold_sum method in the SELECT statement.)

Solution of SQL Interview Question #2

The solution SQL query is:

The trick in this task is that you had to use the COUNT() function two times: first, you had to count the number of images per user, then the number of users (who fulfill the given condition). The easiest way to do that is to use a subquery.

• Write the inner query first! Run a simple COUNT() function with a GROUP BY clause on the event_log table.
• Make sure that you create an alias for the subquery ( AS image_per_user ). It’s a syntax requirement in SQL.
• Eventually, in an outer query, apply a WHERE filter and a COUNT() function on the result of the subquery.

Solution of SQL Interview Question #3

Note: You can solve this task using a subquery, too – but in an interview situation the interviewer will like the above solution better.

Brief explanation:

1. First JOIN the two tables:

Watch out! Use the employee_id column – not the employee_name . (You can always have two John Does at a company, but the employee id is unique!)

2. Then use the AVG() function with a GROUP BY clause — and replace the * with the appropriate columns. (Just like in the first task.)

3. And the last step is to use a HAVING clause to filter by the result of the AVG() function. (Remember: WHERE is not good here because it would be initiated before the AVG() function.) Watch out: in the HAVING line, you can’t refer to the alias – you have to use the whole function itself again!

Prepare for SQL tech screenings by practicing!

If you solved all these questions properly, you are probably ready for a junior or even a mid-level Data Analyst SQL technical screening.

If not, let me recommend my new online course: SQL for Aspiring Data Scientists (7-day online course)  – where you can level up (or brush up) your SQL skills in only 7 days. When you finish the course, just come back to this article and I guarantee that you will be able to solve these questions!

And if you are just about to start with SQL, start with my SQL For Data Analysis series on the blog!

And ultimately, if you feel that you are ready for a junior data scientist position but you want to try out how it works before you apply for a job, take my 6-week data science course:

The Junior Data Scientist's First Month

A 100% practical online course. A 6-week simulation of being a junior data scientist at a true-to-life startup.

“Solving real problems, getting real experience – just like in a real data science job.”

The hard part of these SQL interview questions is that they are abstract. The tasks say to “imagine the data sets” and show only a few lines of them. When you get an exercise like that, it helps a lot if you have seen similar datasets and solved similar problems before. I hope solving the tasks in this article will boost your confidence!

If you have questions or alternative solutions, don’t hesitate to send them in via email and I’ll review them for you!

• If you want to learn more about how to become a data scientist, take my 50-minute video course: How to Become a Data Scientist.  (It’s free!)
• Also check out my 6-week online course: The Junior Data Scientist’s First Month video course.

Cheers, Tomi Mester

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Take-Home Coding Challenge Examples That Will Change the Caliber of Your Applicants

Coding tests greatly increase the quality of applicants who advance into the final stages of technical hiring. They effectively distinguish talented candidates from unqualified applicants early on in the interview process. Coding tests also reveal a lot about candidates’ working style, efficiency, and communication skills. Take a look below at several take-home coding challenge examples that you can use in your next technical interview. 

Take-Home Interview Advantages

Technical interviews usually begin with screening candidates and selecting those who possess the required qualifications on their resumes. Then, candidates go through screening questions that plumb the depth of their skills and experience. Some of these questions might include:

• What relevant technical qualifications and training certifications do you have?
• Do you have experience using...?
• How do you handle criticism or feedback from teammates?
• How would you explain [a technical concept] to a non-tech co-worker? Do you prefer to work independently on a technical problem or figure it out with the help of others?

‍ Such questions probe candidates' deeper understanding of their subject area and interpersonal skills. After this stage, the candidate proceeds to the technical assessment portion, where they solve a challenge live or on record in their own time. Take-home interviews are particularly useful for candidates who are not comfortable with a live test. Likewise, take-home interviews allow engineers and team leaders to review a candidate’s work in detail.

Take-Home Coding Challenge Examples

Take-home challenges depend on the position level in which candidates are applying. Here are a few examples:

Data Structures

• Array: Find a pair with the given sum in an integer array using sorting or hashing.
• Trees: Write a function that deletes a given key within a binary search tree.
• Matrix: Find the shortest move sequence of a knight on a chessboard from its starting position to a destination square. 
• Linked List: Using two lists containing increasing numbers, write a function that merges them into one with numbers in the proper increasing order
• Dynamic Programming: Write a function that divides a given set of integers into two partitions with equal sum

Algorithm Questions

• Implement the Quicksort partitioning algorithm in your preferred language
• Design an algorithm that inserts a node in a sorted list/linked list
• Write an algorithm that deletes a node in a singly linked list
• Write an algorithm that interchanges two numbers in Java without a temporary variable  
• Design an algorithm that counts the number of leaf nodes in a given binary tree 

Web Development

• Build a sample website for your favorite TV show
• Recreate the layout of our flagship product page
• Build a web page with social widgets
• Design a sample mobile app for one of our services using jQuery Mobile 
• Design a portfolio website using your preferred language

Software Engineering 

• Design an app that tracks system bugs
• Develop a sentiment analysis system for a product's rating and reviews
• Design a website chatbot for answering basic queries
• Develop a mobile checkout app with QR code
• Design a web app for scheduling employee shifts

Data Science

• Create a time series forecasting model that predict store sales using historical sales data
• Build a credit score prediction model using a credit scoring algorithm
• Estimate the future price of a product using market trend analysis
• Predict the sale price of a house using given datasets

After the Test

Team leaders and engineers can build on the take-home challenge by inviting the candidate to a live interview after the challenge. This is where the applicant and interviewer go over the code together and discuss important aspects of the test, such as the candidate’s approach to problem solving. Team leaders can give feedback on the output and even code with the candidate in real-time to see how they collaborate with teammates.

Take-home coding challenge examples focus the hiring process on skill and technical expertise. It gives candidates ample time to think and accomplish what they want to do, especially if they are not comfortable being put on the spot with a live test. It also gives team leaders and interviewers a chance to examine the output in detail and make better-informed decisions regarding candidate selection. Lastly, senior engineers and team leaders can build on the take-home coding challenge by providing feedback, asking about candidates’ methodology, and doing a coding exercise together. 

Hire High-Quality Tech Talent with Filtered

Filtered clarifies the technical hiring conversation with skill-based assessment. Our platform offers a range of take-home coding challenge examples covering full-stack, SQL, data science, DevOps, and more. Our technical tests support 30+ languages and are designed to cover multiple skill levels within major engineering disciplines. What’s more, our platform is equipped with robust fraud detection so that you can hire technical talent anywhere in the world with confidence.

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A take home assignment of SQL exercises for internship candidates and interviewees. The assignment is designed to test the candidate's SQL knowledge and problem solving skills. The candidate is expected to solve the exercises and submit the solutions in a SQL file.

teamcurri/sql-exercises

Folders and files, repository files navigation, curri data engineering internship take home assignment.

A take home assignment of SQL exercises for summer 2024 internship candidates

• 📝 Table of Contents

❗ Prerequisites

🏁 getting started, 🚀 submission, 🏋️ exercises.

This repository contains a take home assignment of SQL exercises for summer 2024 internship candidates. The assignment is divided into 2 parts:

• SQL Theory -- Short answer theoretical questions about SQL and databases
• SQL Exercises -- Write SQL queries to solve the exercises

The exercises are designed to test the candidate's SQL knowledge and problem solving skills. The candidate is expected to solve the exercises and submit the solutions in a text file and a SQL file.

Before you begin the setup section (below), you will need to have access to or create a new a GitHub account.

To complete the assignment, you will need to have the following installed:

• Docker Desktop
• DBeaver (Community/Open Source Version) (or another SQL client of your choice)

Step 1: Clone the Repository

Open your terminal and run the following command to clone the repository to your local machine:

Step 2: Make sure Docker is running

Open Docker Desktop and make sure it is running. If it is not running, start it.

To check if Docker is running, you can run the following command in your terminal:

You should see information about your Docker installation if it is running, something like this:

Step 3: Start the Database

Navigate to the repository directory (in the same terminal window)

Run the following command to start the database:

This might take a few minutes to create and populate the database.

Step 4: Connect to the Database

Open DBeaver (or another SQL client of your choice) and connect to the database using the following credentials:

Step 5: Connecting to the Database and Writing Queries

Connecting to the Database:

Writing Queries:

Step 6: Complete the Exercises

For the coding exercises, write out all of your SQL queries in a single file called {first_name}_{last_name}_sql_exercise_submission.sql . You can use DBeaver or another SQL client to write and execute/test your queries.

Please make sure to include a semi-colon ; at the end of each query.

For the short answer questions, write out your answers in a text file called {first_name}_{last_name}_sql_theory_submission.txt and make sure to include the question number before each answer.

To submit your solutions, send over the {first_name}_{last_name}_sql_exercise_submission.sql file and the {first_name}_{last_name}_sql_theory_submission.txt file as a DM in Slack to @Nathan Jones .

If you have any questions or need help with the assignment, please reach out in Slack.

Good luck! 🚀

Theoretical Questions

What is a primary key? What is a foreign key? How are they different?

What is the difference between the order of execution of the clauses in a SQL query and the order of appearance of the clauses in a SQL query? ( SELECT , FROM , WHERE , GROUP BY , ORDER BY )

Briefly explain what a LEFT JOIN is, a RIGHT JOIN is, and an INNER JOIN is. Match each of these join types with the correct Venn diagram representation below. (For example, "Join scenario A is an example of a _____ JOIN ")

What is a "one-to-many" relationship?

Your friend Nathan is telling you that he joined the orders onto the drivers table using each table's driver_id column. Nathan can't figure out why he is seeing multiple entries for the same driver in his result set. How would you explain the issue to Nathan?

Coding Exercises

Note : The Expected Output for exercises without a sorting will not match your output exactly (which is fine). The expected output is just a sample of what the output should look like. The Expected Output for exercises with sorting will match your output exactly.

Question 1. List all orders with their associated id, order times, product names, quantities, and order statuses. Sort the list so the oldest orders appear first.

Expected Output:

Question 2. Find the total number of orders for each user that has placed an order. Include the user's id, name, and the total number of orders. Sort the results by the user's with the most orders. Name the columns user_id , user_name , and total_orders .

Question 3. Calculate the total revenue generated by each product, sorted by revenue. Name the columns product_name and total_revenue .

Question 4. List all products and their last delivery date. Name the columns product_name and latest_delivery_date .

Question 5. Find the number of orders each driver has been assigned to. If there are drivers that have not been assigned to a delivery, make sure they show up and have 0 for their order count. Name the columns driver_id , name , and order_count .

Question 6. Calculate the average time to complete a delivery (in hours) for orders that have been delivered. Name the column average_delivery_hours .

Question 7. Show the total orders and total pending orders for each city where drivers are based.

Here is the Entity Relationship Diagram (ERD) for the practice database. You can use this to understand the relationships between the tables and it will help you write your queries.

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Tips and Techniques for Excelling in Your Time-Limited Take-Home Data Science Assignment

Introduction

Take-home assignments play a crucial role in the interview process for data scientist positions, allowing candidates to showcase their skills and problem-solving abilities. These assignments often come with limited timeframes, making the task daunting. 

At sqlpad.io , we have coached hundreds of clients to prepare for data scientist interviews, gathering valuable insights to help candidates excel in their take-home assignments even with limited time. In this article, we cover essential tips and techniques to help you succeed in your time-limited take-home data science assignment.

• 1. Understanding the Assignment and Time Management

Carefully read and analyze the problem statement. Identify the assignment’s goals and objectives, and clarify any doubts or questions with the hiring team. 

Once you understand the task, set realistic expectations and manage your time efficiently. 

Allocate time for each task based on the limited timeframe and prioritize tasks according to their importance and complexity.

• 2. Choose an Appropriate Programming Language and Maintain Clear Code

Unless otherwise specified, use R or Python, as these are the most common languages in data science. 

Comment your code as much as possible since recruiters assess code clarity. 

Ensure anyone can understand the conclusions of your take-home assignment, even if they are not familiar with the language you used.

• 3. Data Reliability and Cleaning

Never assume that the provided data is accurate. Always verify data reliability and clean it when necessary. 

Some companies even send take-home assignments focused solely on identifying errors within the data. 

Remember that data cleaning is a significant part of a data scientist’s job, especially for those just starting their careers.

Efficient data preparation and exploration are crucial in time-sensitive situations. For data cleaning, focus on handling missing data and dealing with outliers, ensuring your analysis is based on accurate and consistent information. 

When exploring the data, generate essential descriptive statistics to understand the dataset’s features. Identify patterns and relationships using visualizations to make informed decisions during subsequent assignment stages.

Feature engineering is a valuable skill for junior data scientists. Focus on creating impactful new features to enhance your model’s performance. 

To save time, consider using automated feature selection techniques, helping you identify the most relevant features for your analysis.

• 4. Play to Your Strengths

Take-home challenges are often open-ended, so play to your strengths. Depending on your skills, this could mean spending more time on visualization , machine learning , product ideas , or business insights.

• 5. Efficient Model Selection and Development

Quickly choose appropriate algorithms based on your prior experience or recommendations. Consider simpler models for faster implementation. 

When training and validating your models, use efficient sampling techniques and opt for quicker hyperparameter tuning methods. 

For model evaluation, select a single, most relevant evaluation metric and perform k-fold cross-validation to save time while maintaining accuracy.

Avoid overcomplicating the solution. Focus on a few key aspects and ensure the overall message is clear and consistent. Similarly, when building a machine learning model, don’t spend excessive time optimizing its accuracy.

Choose a model, explain your reasoning, and use sensible parameters. Mention what you would do if you had more time to optimize the model.

• 6. Emphasize Business Impact

Focus on the potential business impact of your work. How would the company benefit from your analysis, and what would you recommend as the next step? 

This practical application focus will help demonstrate your value to the organization. 

Communicate your results with simple, easy-to-create visualizations prioritizing clarity over aesthetics.

• 7. Showcase Interesting Findings

If you discover any interesting insights in the data, even if unrelated to the assignment questions, share them. 

Uncovering hidden information can significantly boost your chances of passing the take-home assignment, demonstrating your ability to discover insights the hiring team may not be aware of.

• 8. Prioritize Practical Application over Theoretical Knowledge

A take-home challenge is rarely the place to overemphasize theoretical knowledge unless specifically required. 

Focus on applying your knowledge to practical situations and demonstrating your problem-solving skills.

• 9. Ensure Your Model Fits Well Before Extracting Insights

Before analyzing your model’s coefficients, splits, or variable importance, make sure it predicts well. If your model’s predictions are unreliable, the insights derived from it will be irrelevant.

• 10. Final Submission and Follow-Up

Before submitting your assignment, review your work for completeness and accuracy. Ensure you submit your work on time and be prepared for potential follow-up questions during the interview.

By following these tips and techniques, you can successfully navigate time-limited take-home data science assignments and make a strong impression on potential employers. 

Remember that practice and preparation are essential for success, and the experience gained from tackling time-sensitive assignments will serve you well in your future data science career.

Boost your data science productivity 10x with sqlpad.io , the ultimate platform to master SQL and Python for efficient, high-impact data analysis skills.

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