Freenow by Lyft Data Scientist Interview Questions
& Process

The interviews happened in this order: First, an HR screening. Then, I talked to the hiring manager, which was super helpful to really get what the role is about. After that, there was a technical interview with two data scientists. Then came a take-home assignment, which was open-ended and took me a solid two days to finish. The final stage involved reviewing the assignment with some of Beat's data scientists, where I had to explain my thinking behind my solution. This was followed by two interviews with product and engineering managers, covering behavioral and product management topics, a team fit interview, and a final HR chat. While the whole process felt a bit long and the home assignment could have been a bit shorter and clearer, I genuinely enjoyed the interviews.

The interview process was okay, and they might use your solution. It was pretty straightforward: initial HR screening, then a take-home challenge using the Kaggle taxi dataset. After that, there was a technical interview with two leads, followed by a call with the Head of Data. If you pass these rounds, you'll meet the whole data science team virtually (which happened in my case). Overall, it was a good experience, I made it to the end and met the team. The main thing is whether they'll find someone internally who fits or if they'll prefer someone with an EU visa. Even though everything went well, it felt like a waste of my time.

The interview process started with an HR phone screen, then a product-focused interview with a PM, followed by a technical interview with two ML engineers. After that, there was a take-home assignment. This was followed by an interview to discuss the assignment with the same two ML engineers. Then, another round of product interviews with a PM occurred. Finally, there was a fit interview with a VP and another with an engineering manager. Even though it sounds like a lot, the whole thing took about 4 weeks from application to offer. HR was really responsive and organized everything quickly. The interviews were short, around 30-45 minutes, and very direct. They really dug into the technical details of my past projects, asking about my specific contributions, how I solved problems, and my reasoning. Questions covered statistics, ML, project management in teams, and how these impact the product. Everyone was knowledgeable and asked good, challenging questions. The conversations were good, and I got a feel for the company culture. The take-home assignment was open-ended, using somewhat messy data, and took me about 2-3 afternoons to complete, though it might be harder for less experienced people.