For context: I graduated with a MS in CS in May 2014. Applied through LinkedIn and was later contacted by HR via email asking to schedule a phone screen. Completed the phone interview and was the invited onsite for more interviews. Standard full-day interview process with lunch, etc. Interviewers were all very smart. I did not have difficulties understanding any of them (accents, etc.) as some on Glassdoor have mentioned. Questions consisted of experimental design, product health metrics, statistics, probability, SQL, and (software engineer interview-style) programming questions. Some of the probability and statistics questions were quite difficult. The interviews were hybrid PM/statistician/developer style which made it difficult to prepare for. Note: this is for the Data Scientist, Analytics and not the Core Data Science / Research Team.

Firstly, the recruiter emailed me some questions, including basic inquiries about my background, projects I've worked on, and how I approach product cases. The interview process consisted of two rounds, each comprising a mix of technical questions, behavioral assessments, and product case studies. In the initial round, the focus was on technical proficiency, evaluating my knowledge and skills relevant to the role. This involved discussing past projects in detail, demonstrating problem-solving abilities, and assessing my understanding of key concepts within the field. The second round delved deeper into behavioral questions, aiming to gauge my interpersonal skills, communication abilities, and how I approach challenges in a team environment. Additionally, I was presented with more complex product cases, requiring me to analyze scenarios, propose solutions, and articulate my reasoning effectively. Overall, the interview process provided a comprehensive assessment of both my technical capabilities and my suitability for the role in terms of teamwork, problem-solving, and product understanding.