FAQ: How to prepare for analytics & data science job interviews?
After sending out countless job applications, you’ve finally been invited to a job interview! Congratulations!
Now, how are you going to prepare?
The process I follow, and what I advise to the people that I coach is:
Organize your past experience (STAR!)
Practice the technical stuff
Think about the business
What I do during the actual interview
Originally I was going to send all of this in one email, but it became a very long email, so I’m breaking it into four parts.
The first part: Organize your past experience.
Step One: Keep track of your accomplishments
Hopefully, you have a Hype Doc - if not, start one ASAP.
Now, take a look at the job description - what type of experience are they looking for? What tasks and projects will this role focus on?
Step Two: Brainstorm the experience that is relevant to the role
Create a new document for yourself that lists your past projects and experiences that are most relevant to the role. I would list everything that comes to mind, but you want at least 3-5 examples so you have enough to talk about in interviews. You can include examples from your paid work as well as volunteering, personal projects, school assignments, and more.
Step Three: Summarize your projects
Now, under each of your projects, write out what you did using the STAR method. Try to be succinct. Use the STAR framework when explaining the project during an interview.
Situation: What was the business problem?
Task: What was the output or goal?
Actions: What tasks did you personally do?
Result: How was the business impacted?
Other things to think about—these are common follow-up questions, so I wouldn’t talk about these points in your initial response but have an answer ready in case they specifically ask about …
What would you have done differently?
What challenges or obstacles did you face?
What were the next steps after the project ended?
Step Four: Review before your interview
You don’t want to use this document as a script that you read from during the interview, but it serves two purposes:
Jog your memory during the interview when they ask “tell me about a time you …”
Give you a framework to answer these questions without rambling on for too long about unimportant details.
When you answer questions like these, stick to the STAR format to give a high-level overview, and then conclude with “is there anything specific you’d like me to dive into deeper?”
Step Five: Be succinct
One mistake candidates make is giving long, detailed, rambling answers during interviews. This can be a problem for a few reasons:
You give too much detail about the wrong area. Maybe this interviewer wants to know your methodology and the technical tools you used. Maybe another wants to know more about the business impact.
You spend too much time answering questions and run out of time to cover everything they wanted during the time scheduled.
Being a good communicator is an important part of pretty much every job, especially analytics and data science jobs. Not being able to communicate clearly and succinctly about your own experience won’t position you as a strong candidate.
So, start with your STAR summary, and then ask them for what they want more of.
Stay tuned next week for Part Two: How to Prepare for Technical Interviews.
Need more help? I’m thinking of putting together a job search cohort course - join the waitlist to find out when (if?) it launches!
You can read my answers to past FAQs. Have a question of your own? Reply to this email!