Ho presentato la mia candidatura online. La procedura ha richiesto 4 settimane. Ho sostenuto un colloquio presso Google (Mountain View, CA) nel mese di set 2014
Colloquio
Applied online and got contacted by a technical recruiter. I had to fill about 13 questions first - i guess this was a kind of screening process. and she got back to me 2 weeks later saying that I will have a phone interview. In the phone interview, I answered questions but with the interviewer's hints. The recruiter got back to me a week later saying that she's not moving forward with me as they are looking for candidates with stronger problem solving skills.
- Asked foundational questions about key definitions and terminology to assess baseline understanding of core concepts
- Completed a timed online coding assessment covering practical programming challenges and problem-solving ability
30 minute phone screen with HR, followed by an interview with the hiring manager. HR would not even provide a salary range for the role, which was very weird. The HR rep was not familiar with the role and seemed to be reading from the JD when I asked questions about it.
Ho presentato la mia candidatura tramite segnalazione di un dipendente. La procedura ha richiesto 2 mesi. Ho sostenuto un colloquio presso Google (Seattle, WA) nel mese di ago 2021
Colloquio
Recruiter screen > tech screen > 5 tech sessions at remote "onsite"
Tech screen: all statistics written in easy python
On-site: python for SQL-style queries, one session focused on stats/probability, majority of sessions had some probability in it, some question were extremely open ended, hierarchical statistical models, optimization and creating penalty functions, bootstrapping, small sample statistics
Domande di colloquio [1]
Domanda 1
you are given a discrete probability distribution of children, what is the probability a random women you meet on the street has a sister?
Two variables x1 and x2. They are correlated but aren't the same. X3 = X1-X2 and X4 = X1+X2. What are the coefficients for x1 and x2 if you train logit for x3 and x4
1000 ad videos, 1000 human raters
Assess the quality of videos, 100 randomly selected videos to each rater, Rate video between 1 (bad) and 10 (good) quality. How would you rate these? What are the pros and cons of your strategy?
clustered statistical modeling question about how you would set data up for this model and what model you would use.
