DataRobot Interview Questions
& Process

Avoid this place if you care about your time. While individual interviews were fine and the engineers knew their stuff, the overall process was disorganized. It was supposed to take 1-1.5 weeks, but got rescheduled a few times, messing up my deadlines. I had to chase them, and I had to reject another offer due to their expired deadline. I told the recruiter I had other offers and a deadline, and they said they'd decide the next day. That didn't happen, and I suspect they would have forgotten about me if I hadn't followed up multiple times. The whole thing took a month. After 5 rounds (including the initial HR chat), I barely learned about the team (random interviewers) and got a generic rejection. Also, like others said, it seems best to show minimal personality to pass. The process felt scripted, and there was no point connecting with interviewers since the final team was different. I guess sharing personal experience with the Hiring Manager backfired. Wish I knew that, so just stick to the scripted behavioral talk.

First, there was a recruiter call where they checked if I met the basic requirements, asked about my project management methodology experience (like Agile and Waterfall), the kinds of projects I've handled (especially in software, data science, AI/ML), and my interest in DataRobot. Expect to discuss salary expectations here. It was a mutual fit check. Next, I spoke with the hiring manager. This was more about how I think as a PM rather than just my resume. They asked behavioral questions like handling difficult stakeholders or recovering a troubled project, to assess my problem-solving, communication, and leadership skills. I used the STAR method for my answers. We also talked about the specifics of the PM role at DataRobot, including the team, projects, and potential challenges. I asked them questions about their processes and expectations. Finally, there was a panel interview with about four people: the hiring manager, a product manager, an engineer, and someone from data science. The product manager asked about my experience with roadmaps and requirements. The engineer wanted to know my understanding of SDLCs and communication with tech teams. The data science person was curious about my experience with data projects and AI/ML knowledge. It was a conversation, not just Q&A, to see how I think on my feet and collaborate. They also gave me a mini-case study about a project scenario and asked how I'd handle it, to see my planning, risk management, and prioritization skills.

I applied online on April 16th, 2024 and heard back on April 18th for an interview with the recruiter on April 23rd. This first interview was to see if I was a good fit for the role and if the role was a good fit for me. Next, I interviewed with the hiring manager on May 1st, which went great – their approach was just like mine, so I felt really comfortable. Then, on May 3rd, I had a third interview with a CSM peer. This person was knowledgeable, humble, and really nice, making it a great experience. The final interview was with the VP of Account Management and Renewals on May 6th. They were also super nice and shared the same great qualities as the CSM peer. By this point, I was sure I wanted the job because I enjoyed talking with everyone. On May 8th, the recruiter emailed with an offer, which was fantastic news! I really appreciated how efficient the hiring process was, and the communication with the recruiter, Ariel, throughout was brilliant. Overall, it was a really great interview experience.

We had 5 interview rounds in total. First, an HR interview for about 30 mins where we talked about my favourite project, motivations, right to work, etc. Then, an interview with the Head of Data Science (45 mins) - they wanted to understand motivations, why DataRobot, technical capabilities, and mostly get to know me and how I'd perform in the team. After that, an interview with the Head of Sales (45 mins) - they wanted to understand motivations, discuss aspects of myself that aren't on my CV, talk about experience in sales, the culture at DR, etc. Then, a technical interview with a Data Scientist (45 mins) - they asked questions on feature engineering, big data management, how to handle common data issues, and explain the need for cross validation, etc. Lastly, a presentation to a Panel (45 mins) - 15 mins to get to know me, 15 mins to present to 2 interviewers, and 15 mins for them to ask some questions and provide feedback.