Me postulé en línea. El proceso tomó 1 día. Acudí a una entrevista en Google en jul 2019
Entrevista
Application
I was reached out directly by another Quantitative Analyst for tech screen. He was very late when he called me and told me since we are late, lets begin and started asking questions directly. Questions were easy but he would complicate it by asking weird questions around it.
He didn't introduce himself nor asked about my background and I had to ask those things myself when he said do you have any questions? I can't believe this is how Google conducts interviews without any recruiter and some guy reaching out directly who is not punctual and doesn't have any etiquette to introduce himself or tell about team and role. (Foreign accent), It's been weeks since I interviewed and there is no feedback or update as I expected.
Also, you cannot expect someone to solve math problem verbally when formula is complicated and involves square root calculation
Preguntas de entrevista [1]
Pregunta 1
What is p-value and explain to 5 year old?
Calculate p-value verbally with a problem question.
- 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.
Me postulé a través de una recomendación de un empleado. El proceso tomó 2 meses. Acudí a una entrevista en Google (Seattle, WA) en ago 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
Preguntas de entrevista [1]
Pregunta 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.
