NIO Data Scientist Interview Questions
& Process

The phone interview covered fundamental machine learning knowledge and some easy Unix commands. The onsite involved meeting four team members. They were interested in my experience with modeling and big data tools and how I'd use them for their products. It wasn't as tough as I expected for a top company. The management questions weren't quite at the right level, or they weren't very engaged. The recruiters also weren't the most professional, which gives you an idea of the company culture.

Got contacted by a recruiter after applying on their site. Then had a phone screen with a principal scientist where they went over my resume and asked about my past projects. I also had to solve a coding problem in a shared editor. There was a quiet period after that when I didn't hear back about the results. Then, Geno, a recruiter I really liked, set up another phone screen with a principal scientist from a different team. This one was a deep dive into one of my projects, looking at all the practical details. They told me the next day I'd have an on-site interview, which was scheduled for two weeks later and they covered travel and hotel. The on-site itself had six 45-minute interviews, including a lunch chat. These interviews covered my research, core machine learning and deep learning concepts, and some whiteboard coding problems. They also included a case study, which was pretty cool. I got the impression it's a very collaborative place to work, and they want you to be that way too. I got an offer a few days later and accepted. Geno and Michelle were great at keeping me informed throughout the whole process, which actually moved really fast once we got past that initial waiting period. They were super easy to work with.

I found the role on LinkedIn and applied. The recruiter responded the same day and set up a technical phone interview for the following Monday. The phone interview involved algorithm and math questions. The recruiter replied again on the same day and scheduled the onsite interview for Friday. The onsite interviews were with four team members: a Sr. Data Scientist, the VP of Data Science, and two Data Scientists. They were very talented and welcoming. The questions covered different areas. The entire interview process felt very systematic, logically progressing from easier to more difficult questions.