Q. What part of this job will be most challenging for you?
I know I’d have a team of six employees in this position. In the past, delegating has been challenging for me. I don’t want to overload my employees. With that said, if I don’t delegate, I run the risk of overloading myself with work and giving the impression that I don’t trust my employees. I’ve addressed this challenge by ensuring open communication between myself and my team, so I’m clear on their workload, the types of responsibilities that interest them, and addressing why I’m delegating tasks and my expectations. I’ve also taken some training courses on managing that address delegating effectively. These efforts have helped, and I now delegate more easily and confidently.
Additional questions related to your qualifications, work history, and job performance:
Q. How do you handle failure?
I appreciate that failure is inevitable and tend to define failure differently for each scenario. Generally, I first admit to the failure and take responsibility. From there, I assess what went wrong and how it might have been avoided to ensure it doesn’t happen again.
Additional questions about you that you might be asked:
Competency-based, behavioral, and traditional interview questions
Interview questions typically fall into one of three categories, which are:
Preparing for a Data Scientist Interview
It’s not uncommon for a data scientist applicant to go through three to five interviews for the role. This can include a phone interview, Zoom interview, in-person interview, and panel interview.
As you might expect, many of the interview questions will focus on your hard skills. However, you can also expect questions about your soft skills, as well as behavioral interview questions that assess both your hard and soft skills.
Here’s how you can prepare for your data scientist interview.
Start by brushing up on the fundamentals of data science. Review:
Jenna Bellassai, lead data reporter at Forage and former data scientist at Guru, advises applicants to “review fundamental programming and machine learning concepts. Be prepared to describe your contributions to previous projects.”
While part of your interview prep likely involves researching the company, Bellassai says that to prepare for data science interview questions, you should also “think about what the company’s data may look like, what technical challenges they may face, and where machine learning models could play a role in their business. If you have experience with a niche technology or modeling approach that the company uses, be prepared to speak about it.”
Most interviews include questions about the specifics of the role, and a data scientist interview is no different. Bellassai says you can expect technical questions on these topics:
Bellassai also notes that during the interview, you may have to solve a coding problem or draw an architecture diagram.