Delivery Hero Data Scientist Interview Questions
& Process

I've interviewed with this company multiple times, at least three, and each time the process was quite long, usually involving four stages: first, a recruiter call, then a technical round, followed by a deep-dive interview, and finally a bar-raiser round. I often passed all the stages, but afterward, I was consistently told that the position was on hold or would be reopened later. In one instance, I was explicitly told I passed the third stage, but the process concluded without a clear reason for why I wasn't advanced. Even with positive feedback, I never got specific explanations, which was frustrating. The interviewers were professional, but the lack of transparency and the lengthy process made it disheartening. It would be great if they could streamline things and offer clear communication or feedback, especially for those who reach the final stages.

It was a pretty long interview process with five stages: first, HR (30 mins), then the hiring manager (1 hour), followed by three to four technical rounds (1 hour each), and finally a Bar Raiser interview (1.5 hours). Since each round happened about a week apart, the whole thing took at least 1-1.5 months, which was mentally tough and added pressure. They could combine some rounds to make it faster. Everyone I spoke with was really friendly and helpful, and the communication with HR and scheduling were smooth and fast. Organizationally, it was perfect. The role focused on NLP, and the technical questions usually started with my experience and projects, then went into deep dives. They asked for new ideas and approaches to unclear problems rather than textbook questions like 'how transformers work.' This was a good but challenging method because there's likely no single right answer. There was a big focus on system design, which I wasn't very familiar with.

The interview process had 5 stages: an initial screening, a live coding session, a data project discussion (covering approach, variables, and potential issues), a chat with the hiring manager, and a final hiring alignment. The first stage was a 30-min intro chat. The live coding and data project were back-to-back over 3 hours, which was pretty draining and the interviewers seemed unprepared. The coding part was confusing because they offered solutions that didn't clarify the task. The data project part was even rougher – the interviewers didn't seem to grasp the solutions proposed, making me explain basic concepts in simple terms, which took extra time. They asked repetitive questions like 'how do you build a machine learning model,' which felt too basic for the role and had already been covered, suggesting they weren't really listening. I didn't make it to the fourth stage, likely due to the interviewers' limitations. While I know interviews can be tough, the lack of preparation and understanding made it hard to show what I could do. It was a missed opportunity for everyone.