Do you have an upcoming data science job interview? Whether you’re an experienced head or new to this, interview preparations follow the same formula. There are several key things to know, prepare and understand before the big day.
Here’s what to prepare so that you can prove you’re the right candidate for your next data science job.
Data science interview prep is all about knowing three key things:
Make sure you know what will be expected of you in the interview. You can do this by checking with your recruiter.
For the first round of interviews, you might not need to dive too deeply into your technical knowledge. If this is the case, get ready to tell your career story. That will help the interviewer know what you can bring to their company. Demonstrate your communication skills rather than focusing solely on data wrangling.
For later stages in the recruitment process, you may want to prepare more detailed examples of your experience.
If it’s not the first interview, you’ll usually have to prove your technical skills. At this stage, you might meet your potential manager or head of department. The interviewer will want to know your data scientist skills in detail. They may also ask about your sector experience and will want to understand your problem solving skills and data driven decision making.
Latter-stage data science interviews can vary from company to company. This stage can include technical questioning and sometimes coding tests, so you should be prepared for any outcome.
It doesn’t matter how far along you are in the hiring stages, there’s one thing you absolutely need to know: the organisation you’re interviewing with. Take a look at their website and social media. Research their products, clients and achievements.
You can also research the key trends in the organisation’s industry sector and what their main competitors are doing. Consider any actionable insights you can infer from industry trends. This approach will give you a great idea of what would be expected of you in the role. Understanding your next data science job will inform what you should prove in your job interview.
Make sure you’re ready for some common data science interview tests and practical topics. Demonstrating a clear understanding of the following skills will convince your interviewer that you’re the right candidate:
Above all, make sure you highlight your technical skills andcinclude examples of where you’ve used them. You should have listed the programming languages you’re comfortable with on your CV, so you may be asked to demonstrate your knowledge here.
If you’re new to the data science industry, it’s particularly important to demonstrate strong programming skills. You can offset a lack of experience with valuable qualifications.
If you’re an experienced data scientist, it’s important to demonstrate up-to-date knowledge. Prove that you continually review and improve your programming skills.
Any data science role will require handling large data sets. The interviewer could ask you to give examples of occasions where you’ve done this in the past. They may even want to test you with a technical exercise.
If you can, refer to specific examples from previous roles. The STAR method is a great way to structure your interview responses in this instance.
If you’re entering the field of data science with limited experience, prepare to talk about your mathematical background. Proving strong foundational knowledge of statistical modelling is often the key to landing entry-level roles.
Even if you’ve held data science jobs in the past, it’s important to showcase your understanding of the wider context. Try not to get too caught up in the everyday details.
Make sure that you’re comfortable discussing basic machine learning algorithms. You may need to explain how they work and when they might best be applied to specific tasks.
Whether you’re a new data scientist or further along in your career, machine learning is an important new subject area for all roles.
You’ll need examples of projects that you have delivered and the problems you have solved. Having a portfolio of these projects you can showcase in an interview is an excellent idea. Just make sure you are not breaching any previous confidentiality rules at your past or current organisations.
From your portfolio, explain your experience step by step:
If this is your first data science job interview, consider any extra-curricular projects that you could describe.
If you have a technical data science job interview, you can find additional advice here.
While you might be planning how to answer questions, it’s also essential to have questions ready to ask the interviewer. Responding with relevant questions shows that you’re genuinely interested in the role and company. Plus, if you have any doubts or clarifications, your interview is a great time to get more information.
Good questions to ask in your data science job interview include:
By asking these questions, you’re not only discovering information for yourself. You’re also showing the interviewer that you’re engaged, interested and keen. This approach will help you to connect on a personal level as well as professionally.
The key to success in your next data science job interview is to prepare well. Gather all the information you can, understand how to point out your key strengths and learn about your potential employer. Then, you’ll be ready for anything the interviewer asks.
Looking for a role in data science? Find your next job with Hays.
Martin Pardey Senior Business Director Hays Technology – South East UK
Martin Pardey is a Director for Hays Technology in the South East, the World’s largest specialist recruitment company. Martin has 15 years’ experience at Hays, specialising in the last few years in the Business Intelligence and Data Analytics sector.
