Lyft Data Scientist interview questions

Got a call back from the recruiter after online resume application. Initial phone screen with HR regarding the role, team and your background fit. One 30-45 min phone screen with data scientist which is mostly about a business case study and your technical experience and projects. Next was a 48 hours data challenge, with multiple questions and subquestions. it has a good balance between the technical and business side of the problem. This is probably the hardest part of the interview process as you have to build a coherent story with your analysis while answering all the questions asked. Followed by half a day of on-site interviews data-challenge presentation, 2 business case studies, stats and probability, technical (SQL and R/python) and values and cultural fit interviews with varied team members with different experience level. Overall the onsite experience was pleasant, but I struggled in one of the business cases as the question was described in a line as opposed to a business situation in other interviews at Lyft or other firms. This either meant I had to ask multiple questions or make numerous assumptions. Also, the way the interviewer wanted to approach the problem was radically different to what I proposed and it just didn't go well with the interviewer. I must point out that he was extremely polite and not at all condescending throughout the 30 mins. Stats and technical interviews were pretty easy if you know business applications of key concepts, their variants and data manipulation using SQL(window functions). Overall a great bunch of people to talk with, was given quick results and accommodated my schedule. The recruiter also called to give feedback after conveying the decision. I still feel more business context should be given during business case studies. All the questions are related to Lyft's business model and their product