Google | Data Scientist | Zurich | Aug 2021 [Reject]
Summary
I had a two-stage interview process for a Data Scientist role at Google in Zurich, consisting of a recruiter call and a technical phone screen. Despite performing well in data intuition and coding, a deep dive into Bayesian statistics led to my rejection after the first technical round.
Full Experience
My interview process for the Data Scientist role at Google in Zurich began with a 30-minute recruiter call. This call primarily focused on understanding my background, where I was asked to describe my previous projects and explain my motivation for applying to Google.
I then proceeded to a 1-hour technical phone screen, which was divided into three sections: data intuition, statistics, and live coding. In the data intuition section, the interviewer asked me about designing a survey, which had a strong statistical basis. The statistics section delved into concepts like Bayesian statistics and confidence intervals. Finally, the live coding challenge involved sampling from a normal distribution, for which I was permitted to use a Python library.
I felt I performed quite well in both the data intuition and coding parts. However, the interviewer explored Bayesian statistics in considerable depth, and I eventually struggled to provide satisfactory answers. Despite feeling generally positive about my performance, I received a rejection after this first technical round. The recruiter did encourage me to reapply after a six-month period.
Interview Questions (4)
Describe your previous projects and experiences relevant to the Data Scientist role.
Explain your reasons for applying to Google and this specific Data Scientist role.
How would you design a survey, considering statistical principles and potential biases? This question was mostly statistics-based.
Implement a function or code snippet to sample from a normal distribution. I was allowed to use a Python library for this task.