Datadog Data Scientist Interview Questions
& Process

First, there was a hackerrank test, which was pretty easy. Then, an HR interview. After that, a Leetcode test with a Software Engineer from the company, also quite easy. This was followed by an interview with the data science team. Finally, they made an internship offer.

First, I had a phone screening call with a Recruiter where we talked about my past experience and what I'm looking for now. Then, I moved on to the Technical Fundamentals interview. This part focused on anomaly detection in time series data and OLS regression, specifically considering computational constraints.

The process included a 30-minute intro meeting and a 1-hour screening interview, which was a Python coding game. Then there were 4 technical interviews, each lasting 1 hour, spread over several days. These covered coding games, behavioral questions, experience, data science fundamentals, data analytics, and ML system design. Everything was in English, though some interviewers also spoke French. Specifically, the coding game involved programming a function similar to the Datadog environment. The behavioral part focused on recent project challenges. The experience questions delved into recent/current projects and methodologies. Data science questions tested fundamentals, algorithms, and data problem-solving. The data analytics portion involved analyzing a notebook with plots and a problem. ML design involved an open-ended architecture problem. Positive aspects were attentive interviewers and sincere answers to questions. On the downside, the interviews were challenging and required significant preparation, with very little specific feedback provided afterwards on areas needing improvement.