6 Coding Questions for a Data Scientist Job Interview (With Tips)
Data science is a new field in the field of technology. During an interview for a job as a data scientist, you might be asked about SQL, Python, applied data manipulation, and basic computer science. But the need for data scientists who know how to code is growing in general, so it’s important to know how to answer these kinds of questions in an interview. This article talks about why hiring managers ask coding questions, gives examples of coding questions for a data scientist interview, and gives advice on how to do well in your interview.
Why do people who hire people want to know about coding?
Data science is a very technical field that involves collecting, cleaning, and processing data so that it can be used. Because of this, hiring managers may ask you questions about how you code. Most of the time, you need to know a little bit about programming and coding in order to do this job well. In the same way, knowing how to code might help you work better with different project stakeholders, like working more closely with engineers to solve problems. Organizations may also ask you to help with projects that involve production code.
But the kind of job you want may affect whether or not a hiring manager asks you about coding. For example, coding questions may be more common in engineering organizations or small to medium-sized technology companies. If you are applying for a job that focuses on machine learning, you may also be asked more questions during the hiring process. On the other hand, you may not be asked about coding if you are interviewing for a job that focuses on product analytics. But as a data scientist, you should still be able to answer questions about coding.
Sample answers to six coding interview questions for a data scientist
When you go in for an interview for a job as a data scientist, the person in charge of hiring may ask you different questions about coding. For example, they might ask you to explain certain ideas, your experience with techniques, or your workflow process. They might also give you real-time coding problems to solve on a whiteboard or computer using a coding simulator. Here are some questions and answers about coding that a hiring manager might ask you during a data scientist interview:
How would you handle an aggregation, a categorization, and a ratio all in the same query?
Aggregations, categorizations, and ratios are three common ideas that a hiring manager might ask you about or test you on. They often put these three ideas together to see how well you know each one and how well you can explain how they work together. Think about how you would solve this kind of problem step by step, and if you have one, give an example from real life.
Here’s what I mean: “I know how to put these ideas to use in SQL. If I had to solve a problem that included all three in one query, I would start by writing the CASE statement. Once I had the case statement, I would add up all the results and then use those results to figure out the ratio. To get a result between 0 and 1, you may also need to change the data type from integer to float.”
Why would you put a subquery in the WHERE clause?
Hiring managers will often test you on subqueries in the WHERE clause or ask you to talk about them. They might ask this to see how well you understand the idea in general and how you’ve used it in the past. Think about a time when you used a subquery in the WHERE clause and give an example.
Here’s what I mean: “You can match columns to rows by using subqueries in the WHERE clause. This makes it easier to get information from different tables. For example, I recently wrote a query that used this kind of subquery to find out which students got the best grade on an exam. The first question told us what grade each student got. The second question told us who got the best grade.”
What kinds of SQL window functions are most often used?
To test how well you know SQL, a hiring manager might ask you about window functions. As a data scientist, it’s especially important for you to know how to use these functions because you’ll probably use them every day at work. Give the names of some common functions and maybe explain how you would use each one.
Here’s what I mean: “One of the window functions I use most often is one that helps me deal with data that changes over time. This is useful for metrics that change over time or trends that change from month to month. The generating statistics window function, as its name suggests, can be used to make simple statistics like medians, percentiles, and quartiles. I use the simple aggregate functions a lot to add up numbers and put them into groups. I use functions that rank them when I need to put datasets in order.”
What do you know about changing the dates?
As a data scientist, one of the most important skills to learn is how to change dates. This is a question that a hiring manager might ask to see if you know how to collect, sort, and understand data. Tell the hiring manager what happened when you changed dates and how you did it.
Here’s what I mean: “When putting together data for my clients, I often change dates. For example, I recently worked with a pizza shop that wanted to know when they get the most orders so they could change the hours of their workers to match. They gave me monthly and daily data, which I used to figure out which hours had, on average, the most orders.”
Explain what a JOIN is.
A JOIN is a common SQL clause that lets you combine rows from different columns based on a column they both have in common. A hiring manager might ask you about JOINs to see how well you understand them and how well you can work with data and organize it in useful ways. You could give an example of a project where you used a JOIN clause in addition to explaining what it is.
Here’s what I mean: “With a JOIN clause, you can combine rows from different tables to get a more complete picture of your data. For instance, I worked on a project for an online store that wanted to combine two tables: one with customer names and order dates, and the other with customer names and order dates. I was able to put all three columns into one table by using a JOIN clause.”
What’s your favorite way to write code?
If you want to be a data scientist, a hiring manager may expect you to know more than one programming language. In your answer, talk about the programming languages you know best. Talk about your favorite one and why.
Here’s what I mean: “SQL and Python are the two programming languages I feel most comfortable with. I like that SQL lets me organize my data in ways that make sense and help me find important insights. But another reason I like Python is that it can be used for a wide range of projects.”
Advice for when you meet a data scientist
To do well at your interview, think about the following tips:
Think back to the beginning
Review simple topics in coding to prepare for your interview. This is very important if the job you want doesn’t require as much coding as your current job does. Things to look into are:
- Review specific data structures, such as arrays, strings, heaps, sets, hashmaps/dictionaries, stacks/queues, and trees/binary trees. It’s also important to learn about algorithms like dynamic programming, recursion, binary search, and sorting.
- Machine learning: Look at both supervised and unsupervised machine learning model families. For instance, look at the k-means clustering unsupervised learning model and study supervised learning models like the decision tree, k-nearest neighbors, logistic regression, and linear regression.
- Review math and statistics ideas that have to do with simulations, such as weighted sampling, Monte Carlo simulations, and simulating Markov chains. It’s also important to learn about prime numbers or ways to divide numbers, like the Euclidean algorithm or how to figure out how to divide natural numbers.
Find out what questions are often asked in interviews.
If you want to be a data scientist, you should think about both common interview questions and technical questions as you prepare for your interview. People should ask you about your strengths, weaknesses, behaviors, and habits. If you think ahead of time about how you might answer technical questions at your interview, you will feel more prepared.
Make a fake interview.
You could practice for an interview with a friend or a trusted peer. Give them a list of questions they could ask and ask them to tell you how well you did. If you can’t find anyone to help you, try practicing your answers in front of a mirror.
STAR stands for:
Use the STAR method to give examples from your own life in your interview. This helps a lot when you’re talking about hard times and how you got through them. Plan a response that talks about the following with this method:
- Start by putting the problem or situation in the right perspective.
- Task: Tell what you’re doing in the situation.
- Talk about what you’re going to do to fix the problem.
- Tell what happened because of what you did to finish your answer.
The person in charge of hiring you may give you real-time coding problems to solve during your interview. Ask them to explain if you’re not sure what they want you to do or if you don’t trust the information they give you. This could help you figure out how to solve the problem and show the interviewer how well you can talk with people.