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How To Prepare for a Data Science Job Interview

How To Prepare for a Data Science Job Interview

All your hard work has paid off -- after searching job boards, LinkedIn and company job listings, you’ve finally landed an interview for a data science position. Whether it’s for a job as a data scientist, a data analyst, or another big data-related position, you’ll want to put your best foot forward in the interview so you have the best chance of landing the job. Even if it’s just for a summer internship or an entry-level position, on-the-job training is a great way to keep learning and launch your data science career.

What do you need to do before your interview? How can you demonstrate your skills and knowledge during the interview? And what do you need to do to make a good impression during your interview, even if you have limited experience in data science? Keep reading to find out.

Do Your Research Before Your Data Science Job Interview

Landing an interview is just one part of the process of getting a job in data science. You’ll also need to pass the interview. Depending on the seniority of the position you are applying for, there may be multiple rounds of interviews, along with practical skill tests or exercises. At the same time, you’ll want to make sure that the company is a good fit for your skills, personality and style.

To begin preparing for your interview, do some research on the company. If you applied for the job directly with a well-known company, you may already know a bit about them. But it’s a good idea to dig deeper before your interview. Do you know what the company uses data science for? Which products are you likely to be working on? Do they already have a well-established data science team, or is this a new initiative for the company?

Answers to all of these questions can help you to anticipate how the interview will go -- as well as help you demonstrate some knowledge of the company itself. Many interviews start off with “tell us what you know about our company.” Being able to answer that question clearly will score you some major points with the interviewer.

Data Science Interviews with Smaller Companies and Startups

Many jobs in data science and data analysis are with small companies and agile startups. These companies are often looking to “disrupt” an established industry by tackling problems in new ways -- especially by using big data and data science.

These kinds of companies can be quite a bit different than larger companies, especially when it comes to their interview and hiring process. And you’ll want to be sure that the working conditions and culture of the startup match what you’re able to give to the role -- many are known for working long hours and abruptly changing directions or even leadership teams.

So to prepare for your interview with a startup, do some research on them. When were they founded? Who are the founders? Have they founded successful startups before or are they new to the game? Where are they with funding? All of these questions can help you to “interview” the company to decide whether it’s a place you’d like to work.

You can also do some research about the company on LinkedIn and Glassdoor. On LinkedIn, you can find out things like how many employees work there, what titles they hold, and how long they’ve been working there. You can also find out about your interviewer, if you know who they are -- what title do they hold, and how long have they been with the company? This can help you to know if you’re talking to someone technical, or in more of a management role, and prepare accordingly.

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Brush Up on Your Data Science Skills Before Your Interview

Before you go in for your data science interview -- especially a technical interview -- it’s a good idea to have an idea of what technologies, skills and experience you will need to be familiar with.

In many cases, the job description will have told you which programming languages you will need to know. But other times, you’ll need to do some research. As you do, you can find out what skills others who work at that company in similar roles are skilled in, and spend some time refreshing your skills prior to the interview.

Many companies use Python for data science. If that’s true of the company you’re interviewing with, use the SoloLearn Python course to practice your Python skills. Or spend some time reviewing data science concepts with SoloLearn’s free Data Science course. You can access either course from the mobile app. This means you can take all of the lessons and practice problems with you anywhere you go and sharpen up your programming skills.

Data scientists are often called upon to explain complex topics to business executives and managers. So you’ll also want to practice explaining the things you’ve learned to others. You can do this with your friends and family -- as you learn new things, share them with others. You can also help other learners through the SoloLearn community forums. Taking the time to explain key data science concepts to others will help you in your interview and as you advance through your career.

Make a Good Impression At Your Data Science Interview

Interviews aren’t just about proving technical skills. They’re also used to determine if you’ll be a good fit for the company in other ways. Many companies talk about their “culture” -- the environment that is promoted by executives, management and workers. For example, Facebook was known for their motto “move fast and break things”, meaning that they value making fast decisions and implementing new ideas quickly.

Other companies, particularly large corporations that have been around for a while, take a more conservative approach to innovation and change. In the 80s there was a saying “no one ever got fired for buying IBM” -- that is, buying the more expensive, less innovative product was much safer than buying something more innovative from a smaller, lesser-known company.

Much as you’ve done your research for your interview, doing this will give you  a good feel for the culture at the company where you hope to work. While you should be yourself, you can highlight parts of your experience that match with the company culture and expectations. For example, at a startup you may highlight an innovative idea that you implemented at a previous job. Or at a larger company, you can mention an accomplishment that shows methodical planning and strategic thinking on your part.

Either way, companies hire people to solve problems, not just to fill jobs. So be sure to show how hiring you will help the company, and you’ll have a good chance at making a good impression.

How To Interview When You Don’t Have Much Data Science Experience

If you are trying to break into a career in data science without much prior experience in the field, don’t give up! Everyone has to start somewhere, and many companies are willing to at least give you a chance especially if they’re hiring for a junior data scientist or junior data analyst position. 

Not everyone who becomes a data scientist needs an advanced mathematics or computer science degree -- many self-taught data scientists have been able to work their way up from junior roles.

If you are trying to break into data science from another career path, be sure to highlight accomplishments that showcase your adaptability, flexibility and willingness to learn new things. This could be a time you were asked to take on a new responsibility or learn a new technology with little training. Or it could be your contributions to an open source project, or even a personal data science project you posted on Github. Any of these things could show your interviewer that you have the willingness and ability to learn about data science on the job.

Be sure to not exaggerate your experience just to make an impression or you risk irritating the interviewer and wasting both of your time. At worst, you could find yourself in a role that you’re not qualified for. Being honest about your lack of experience -- but demonstrating your willingness to learn -- are the best ways to handle an interview as someone with little hands-on experience.

An interview for a data science job can be an intimidating process. But if you do your research, brush up on your skills and have a plan to make a good first impression, you’ll be that much closer to landing your dream job.