Meta Data Science interview questions

Contacted by recruiter over LinkedIn. Set up a time to connect. Further set up a Skype interview with a manager. Based on feedback, recommended me to speak with another recruiter in a different division. Had another skype interview, followed by onsite. Had 4 different interviews in the Onsite round, two focused on Product sense, one technical and one on probability/statistics. The interview seemed like they were looking for people who could be well paid cogs in a machine. The interview schedule was designed with just a 15 min break and ran from 10.15 through 2 pm with little time to grab lunch or being provided one. Most companies either provide lunch if an interview happens to be scheduled during lunch hours or schedule an interview that ends before / starts after lunch time. Also, it seemed solving the actual interview questions mattered less than what an interviewer already predecided to offer as feedback based on their opinions about your resume beforehand. Inspite of claims of it being a very rigorous and fair process, it seems there is lot of inbuilt subjectivity in the process and lot of leeway allowed in interview feedback as well as the hire / no hire decision.

I have two phone interviews with the same processes. Both sections contained three parts: 1. SQL coding; 2. R or Python coding; 3. Statistical questions. SQL and R/Python codings are the same problem. They do prefer you to use Python since my interviewer can't read my R codes.