You’ve taken the course, applied for jobs, and you’ve finally landed an interview for a data analyst role. Now you have to prepare for the big day. Developer Academy is here to help, we’ve got you covered from what to do in the run-up to the interview as well as outlining the types of questions you may be asked.
How to prepare for your big data analyst interview
Interviews can be daunting at the best of times, even more so for those new to the process; but by following these simple tips, you can walk in there with confidence and, maybe, even enjoy the experience.
- Remember that you aren’t the only one who wants to impress
The main thing to remember when preparing for an interview is that this is a two-way meeting. While you are hoping that they like you, they are thinking the same thing. Sure, you want to make a good impression and hopefully be offered the job, but you also want to ensure that the company is as good a fit for you as you are for them.
- Study the job description and the company
Every data analysis role will be different because each company has its own set of problems to contend with, and job descriptions are a gold mine of information. Put your analytical skills to the test and tease out any information that could showcase the types of challenges they will be looking to you to help with and start to think about how you would approach them.
Additionally, research the company thoroughly. This will highlight your dedication to detail and prove that this is a job you are genuinely interested in, rather than a means to pay your bills.
When beginning your investigation, ascertain the following to set you on the road to success:
- How does the company make its money?
- What data sets are they most likely to track?
- What audience/s are they trying to reach?
- Are there obvious pain points they may be struggling with?
It may not be possible to answer all of these questions on your own, but the more you can discover, the better prepared you will be.
- Go above and beyond
While programming isn’t a required skill for this type of work, having a basic understanding could be advantageous. This will make you more desirable to potential employers, help you communicate better with other team members and stand you in good stead should the opportunity to progress arise.
Python is a prevalent programming language at the moment, so this may be an excellent place to start. You don’t have to have mastered the art by the time your interview comes around; you just need to have made a start so you can discuss it in the meeting.
- Bring your portfolio
If this is an interview for your first-ever data analyst role, you will stand out from the crowd if you bring along project examples. When you book onto our data science bootcamp or our software developer bootcamp you will leave with the skills needed to jump into the field AND a portfolio to showcase your skills.
- Research typical data analyst interview questions and have your answers ready
Of course, it is impossible to know for sure what kind of questions you will be asked. But we’ve done some analysis of our own and found some common questions you may be asked:
- What data analysis process would you follow?
- Can you name useful statistical methods for analysts?
- Which data analysis software are you familiar with?
- What has been the most challenging project you’ve worked on, and why?
- Describe the best approach to data cleaning?
- Is there a difference between data analysis and data mining?
- What data validation methods do you use?
- What skills do you hold that will make you a great analyst?
- Can you explain what clustering is?
- What made you choose this career path?
Remember that these questions aren’t being asked to catch you out. The interviewer is trying to gauge your knowledge levels; if you are unsure about an answer, you can always say that you aren’t 100% sure but will get back to them as soon as you can. Then follow through. Accepting that you won’t know everything but being willing to find a solution will leave a much more positive impression than merely guessing.
These simple steps can help you walk into that interview room with confidence and may even result in you landing your first data analyst role.