Ignite Digital Talent

How to prepare for a data science interview.

If you’re a data scientist looking for a new job, the chances are that you have been inundated with calls from recruiters and hiring managers. Your skills are in big demand. Organisations across every sector are looking to leverage the advantage that their data can afford them.

While your skills are very much in demand, walking into a new data science job isn’t a given. You’ll still be up against some stiff competition!

Here are some tips about how to prepare for your next data science interview.

Know what’s coming.

What your interviewer requires of you is very much dependent upon the stage of interview you’ll be attending.  In the early stages of the process, you probably won’t need to be as detailed about your technical skills or your experience.  If this is you, then you should be prepared to talk in quite broad terms about your career journey so far.

Try to think about some career highlights that you can draw on. Did you do a piece of work of which you were particularly proud? What did it help achieve, and what was the impact on the organisation?

However, if you’ve progressed further into the process, you will need to evidence your tech skills.  Your interviewer will want to know detail about your sector experience, technical skills, and your ability to solve problems using data.

Your interviewer’s approach may look different from company to company. However, it is likely to be a process of technical questions and sometimes, coding tests.

Either way, you’ll need to be prepared.

How to prepare for your data science interview.

A great interview begins with significant preparation.

You should

These things will help you uncover what you’ll be doing and what will be expected of you. Armed with this information, you’ll be able to know the skills you’ll need to focus on in your interview.

Prove your data science skills.

To prove to your interviewer that you’re the right person for the job, you should be ready for the following.

Programming.

Data handling and SQL.

Maths and statistics.

Machine Learning Algorithms.

Projects.

Think about your past projects (either at work or as an enthusiast) and be prepared to discuss the problems you’ve solved.

For a few, think about answers to the following questions.

If you can, and you aren’t breaching any confidentiality agreements, take along a portfolio of these projects you can showcase in an interview.

From good to great.

What separates a good interview from a great one?

The answer lies in your ability to really communicate your suitability for the role, and company. It is not enough just to show technical ability. Your interviewer wants to know you are the right hire, and this includes demonstrating that you have the desire to make a real impact.

It’s likely that your interviewer will give you a chance to ask questions at the end of your data science interview. You should take this as an invitation to demonstrate your interest in what you can help the company achieve.

You may like to spark up a conversation around this by using these starters.

Are you looking for a new data science job? We can help. Reach out to us today to chat about our data jobs.

Or perhaps you are considering a career in data science? In our CV Essentials mini-series we cover data science here.