Candidatei-me online. O processo levou 2 meses. Fui entrevistado pela Google (San Francisco, CA) em jul. de 2016
Entrevista
There were one email, one phone screening, one tech phone interview and one on-site interview comprised of four tech interviews and one chance to talk to the employer during lunch time. The staff were very nice, the technical people are also easygoing, they are knowledgable and trying to guide me during the process.
Perguntas de entrevista [1]
Pergunta 1
technical stuff covering a lot of areas, very comprehensive
- 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.
Candidatei-me por indicação de um funcionário. O processo levou 2 meses. Fui entrevistado pela Google (Seattle, WA) em ago. de 2021
Entrevista
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
Perguntas de entrevista [1]
Pergunta 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.
