Tech industry interviews are often quite different from the traditional interview. You will probably end up answering some standard questions, like "tell me about yourself," but most of your interview will focus on your knowledge and experience as aData Scientist. You may even have multiple interviews, including a technical interview designed to showcase your work in action. While there's no way to predict exactly what you'll be asked, these common data science interview questions are a good place to start for pre-interview prep.
Describe how you organize big data sets.
Questions that focus on the nitty-gritty of your work processes should be answered in a straightforward way, but you should also provide useful detail. It's helpful to provide a specific example. Talk about a specific data set you worked with, and describe the process you used to organize and clean up the data. Don't worry about being too specific, but do keep the answer reasonably short.
If you were asked to teach data science basics to coworkers from a different department, what concepts would you cover?
Questions like this don't necessarily indicate that you'll be expected to be a data science teacher at work, but they might. Either way, this question is designed to evaluate a number of different things, including your breadth of knowledge, level of expertise, and willingness to help others.
What data science or data visualization books or blogs do you read?
This isn't a question that's likely to come up in a technical interview, but tech companies often like to find out whether your finger is on the pulse of the industry in general. Reading about your field shows your enthusiasm for the subject and proves that you like to think about it. You don't need to rattle off an impressive list. One or two can be fine as long as you have a compelling reason why you like those particular sources over others.
What are your favorite programming languages to work with?
Simply knowing stats may not be enough for many data science jobs, particularly in the tech industry. You'll need to know Programming for Data Science as well. If you are currently stumped by this question, it may be a good idea to take some classes in programming specifically for data scientists so that you can become familiar with different languages and how they're used in practice.
After you've learned the necessary programming skills for data science jobs, you should approach this question as an opportunity to showcase your depth of knowledge. Do this by giving a concise example of why you might prefer one language to another rather than trying to teach your interviewer all about it. He or she likely already knows. They just want to find out what you know. These questions give you an opportunity to have a collegial conversation with your interviewer. Don't feel like there's a definitive "right" or "wrong" answer.
Tell me about a time you had to learn a new skill in order to complete a data science project.
Experiential interview questions really give the interviewer a picture of who you are as a data scientist. This question in particular shows whether you've faced challenges in your career and, if you have, how you handled it. You should have a handful of anecdotes prepared for your interview so you can give useful responses to questions like this. Think about the most challenging projects you've worked on, and be prepared to talk about them in detail if asked.