“I’m a data scientist, and I get asked the same questions over and over again. Here are 30 interview questions that I hear most often.”
“The following is a list of some of the most common interview questions asked to Data Scientists in an interview setting.” “Hopefully this will help you prepare for your own job interviews!”
1. What is a data scientist?
A data scientist is someone who has the skills to analyze large amounts of data and find patterns and trends. They are able to use this information to make business decisions.
2. What do you do as a data scientist?
As a data scientist, you would be responsible for analyzing data to find patterns and trends. You would then use this information to make business decisions.
3. What are some of the tools that you use as a data scientist?
Some of the most common tools used by data scientists include SQL, Hadoop, Python, and R.
4. What is your experience with SQL?
SQL is a language used for managing data. As a data scientist, it is important that you are familiar with this language.
5. What is your experience with Hadoop?
Hadoop is a platform used for managing large amounts of data. As a data scientist, it is important that you are familiar with this platform.
6. What is your experience with Python?
Python is a language often used for data analysis. As a data scientist, it is important that you are familiar with this language.
7. What is your experience with R?
R is a language often used for data analysis and visualization. As a data scientist, it is important that you are familiar with this language.
8. Can you tell me about a time when you had to analyze large amounts of data?
As a data scientist, it is very common for you to analyze large amounts of data. One example would be the analysis that took place during the 2016 presidential elections.
9. Can you tell me about a time when you had to make a business decision based on data?
As a data scientist, you will often be called upon to make business decisions based on data. One example would be the decision to shut down a company’s website during peak hours.
10. What is your experience with analytics?
Analytics is the process of extracting insights from data. As a data scientist, it is important that you are familiar with this process.
11. What is your experience with machine learning?
Machine learning is a field of computer science that involves teaching computers how to learn from data. As a data scientist, it is important that you are familiar with this field.
12. Can you tell me about a time when you had to use machine learning?
As a data scientist, it is very common for you to use machine learning. One example would be the use of machine learning to predict how a customer will behave.
13. What is your experience with data visualization?
Data visualization is the process of transforming data into graphs or charts. As a data scientist, it is important that you are familiar with this process.
14. Can you tell me about a time when you had to create a graph or chart?
As a data scientist, it is very common for you to create graphs or charts. One example would be the creation of visualizations to show how customers interact with a website.
15. What interests you about the position?
The position of data scientist is very interesting to me because it allows me to use my skills in data analysis and machine learning.
16. Can you tell me about a time when you had to use statistics?
As a data scientist, it is important that you are familiar with statistics. One example would be the use of statistics to analyze survey data.
17. What is your experience with modeling?
Modeling is the process of creating mathematical or statistical models of real-world phenomena. As a data scientist, it is important that you are familiar with this process.
18. Can you tell me about a time when you had to create a model?
As a data scientist, it is very common for you to create models. One example would be the creation of a model to predict how a customer will behave.
19. What is your experience with data mining?
Data mining is the process of extracting valuable insights from large data sets. As a data scientist, it is important that you are familiar with this process.
20. Can you tell me about a time when you had to use data mining?
As a data scientist, it is very common for you to use data mining. One example would be the use of data mining to find patterns in customer data.
21. How do you approach a problem?
I like to approach a problem by first looking at the data and then doing some preliminary analysis before creating a final report.
22. What kind of problems do you enjoy solving?
I enjoy solving problems that involve finding patterns in data such as customer behavior or type of customers.
23. What is your experience with Python?
Python is a language often used for data analysis and visualization. As a data scientist, it is important that you are familiar with this language.
24. Can you tell me about a time when you had to analyze large amounts of data?
As a data scientist, it is very common for you to analyze large amounts of data using languages such as Python and R. One example would be the analysis of customer data to determine why customers leave.
25. What is your experience with R?
R is a language often used for data analysis and visualization. As a data scientist, it is important that you are familiar with this language.
26. Can you tell me about a time when you had to analyze large amounts of data?
As a data scientist, it is very common for you to analyze large amounts of data using languages such as Python and R. One example would be the analysis of customer data to determine why customers leave.
27. Describe how you work under pressure in an unfamiliar computer environment?
When working in an unfamiliar computer environment or under time constraints, I like to take my time to explore the software and try to familiarize myself with it before starting my project.
28. What is your experience with data modeling?
Modeling is the process of creating mathematical or statistical models of real-world phenomena. As a data scientist, it is important that you are familiar with this process.
29. Can you tell me about a time when you had to create a model?
As a data scientist, it is very common for you to create models. One example would be the creation of a model to predict how a customer will behave.
30. Have you ever done any predictive modeling?
Predictive modeling is the process of using past data to predict future events. As a data scientist,
