Preparing for Quantitative Analyst at Google
Hello, If possible can anyone let me know how to prepare for quantitative analyst position in Google. Currently I work as BIE at Amazon and prior to it as Business Analyst. On Glassdoor I could only see probability related questions. Any inputs.
Yup. AB testing, hypothesis testing. ML concepts like clustering, regularisation, outlier detection, random forest. Also SQL, R/python coding.
In R and python what all packages should I know very well,
Python - pandas, numpy, scikitlearn, matplotlib, seaborn, tensorflow, keras R - tidyr, dplyr, caret, glmnet, gbm, rocr, tree/rpart, ggplot2 As far as I know, they ask you ml algorithms theory but the coding should be basic data manipulation through pandas/numpy or tidyr/dplyr. They don't make you code ml algorithms.
They focus a lot on stats at intermediate level (think differences between MLE and MAP sort of stuff)!
Can any one who has cracked google quantitative analyst interview explain what interview rounds will be there ? And also can some one point to good resources for the preparation.
Did you find any good resources?
I have worked with R and Python a bit, but is there any good way for practising and solving interview based problems. Like Leetcode for R and Python
Did you find something?
Don’t be fooled by the “analyst” in its title. It’s targeting stats PhD. If you’re a BIE at Amazon, it would be really hard.
I understand, but if I prepare for Quantitative Analyst at Google, that should make me well prepared for rest of the data scientist jobs as well.
Honestly no. Data scientist is not well defined in different companies. Google QA really dives deep on your statistical knowledge. Just my 2 cents.
How was the interview?
A few stats topics will be covered depending on the team, but the one that I saw consistently came up is AB testing/ experiment design/ hypothesis testing.