J'ai postulé via la recommandation d'un employé. Le processus a pris 4 semaines. J'ai passé un entretien chez Google (UC Berkeley, CA) en août 2015
Entretien
I got referred by a Googler for several positions. This Quantitative Analyst role has been the only one that contacted me for an interview. I got contacted about a week after I was referred. First thing was to respond to a questionnaire that asks questions like what tools you use for data processing and what data set size you have worked with. Then a 45-minute technical phone screen was scheduled. The recruiter sent useful information about what to expect and tips to prepare. The interviewer was nice and interacted actively. Questions went from theoretical to more open-ended. Data intuition was tested. There was no coding question. I was not advanced to the next round.
Questions d'entretien [1]
Question 1
A coin was flipped 1000 times and there were 560 (not sure if this was the number) heads, do you think the coin is biased? What if it was only flipped 10 times and there were 6 heads?
- 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.
J'ai postulé via la recommandation d'un employé. Le processus a pris 2 mois. J'ai passé un entretien chez Google (Seattle, WA) en août 2021
Entretien
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
Questions d'entretien [1]
Question 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.