Daybreak Data Scientist Interview Questions
& Process

I applied online and the whole thing took over a week, with 4 rounds total. First was a phone call about my background and interests. Then, a technical interview with the Director of Data Science. It started with me introducing myself, and then they described the role and team. They asked about Python packages I've used and some coding/basic ML questions. Round 3 was another technical interview, this time with a Senior Data Scientist. We did introductions and talked about my projects. They asked ML/DS questions, including the math behind ML algorithms, and about my experience with real-world data and how I'd approach use cases. The last round was a cultural fit chat with the HR head, a casual call to talk about the company's vision and values and see if they matched mine.

Applied Dec 5, 2019, and the process took nearly 4 months. Had a phone interview with HR on Dec 11th, followed by a technical round that I passed. Then, a take-home challenge in the second week of January, which I also passed. Was told an onsite interview was coming soon. A month later, still no word on the onsite. Upon following up, they switched the onsite to a video interview. I agreed and waited for scheduling. Despite HR proposing time slots over two weeks, nothing happened for another two and a half months. Eventually, a video interview was scheduled, which I enjoyed with the team. Weeks passed with no updates. I reached out, and HR said she'd finalize things. Finally, HR called to say the position was no longer available due to a company strategy shift, which seemed odd given its availability elsewhere. My experience with Noodle.ai HR was disappointing due to the slow pace and lack of clear communication, despite enjoying the team conversations.

I applied through the careers page. The process had 5 rounds. Round 1 was an HR phone call for 20 minutes. Round 2 was a 1-hour technical interview with the Director of Data Science. They talked about the team and role, then asked 2 questions: a Python coding question and an ML business problem that needed some thought. Round 3 was a 1-hour technical interview with the Principal Data Scientist. We went deep into my CV and almost all my ML projects were discussed thoroughly. I was asked many questions about my modeling choices, their benefits and drawbacks, and other options I could have used. They also asked about the math behind ML algorithms. Round 4 was another 1-hour technical interview with a senior Data Scientist. After introductions and discussing my experience and projects, I had to solve a Python coding problem. Then, a couple of my projects were discussed in detail, and I was asked many Machine Learning questions, focusing again on the math behind algorithms and how to use them for real-world data. Round 5 was a 30-minute cultural fit round with the HR head. It was a casual chat about the company's vision and values to see if they matched mine. I really enjoyed this talk!