Looking for information on the google DS process - does anyone know how it works? can you share resources or questions if you have them?

been a while since I interviewed and ended up going with a different company. I rmember them asking me a probability questionâ€¦it was something like â€śthere are (x amount) of cards with (x different colors) and (x different numbers). each color has one of each number. if you pick 2 different cards, whatâ€™s the probability that they arenâ€™t the same color or number?â€ť

sorry if that sounds confusing, I dont remember the number of cards/colors and stuff. Other than that, just brush up on your basic data science knowledge, learn about Googleâ€™s culture, etcâ€¦good luck!

Hereâ€™s a case question I got:

Google wants to increase the font size of the sign up button on Gmail

- How do you choose KPIs to track?
- How do you select the size of the experiment?
- Whatâ€™s the time interval you want to test?
- How do you plan on designing the reporting dashboard?
- How can you confirm the effects are real and long term?

Other interview parts (high level and non-specific because of NDA)

Statistics: asked about terms, should be highly proficient in basic concepts (p-value, confidence interval, logistic regression, linear regression).

A/B Testing: understand be able to explain pitfalls, biases, and edge cases

SQL: extensively practice calculation topics

ML: know what model to use when, be familiar with basic assumptions, consider pros and cons of each model, consider errors that might exist

Behavioral: concisely talk about past experiences, checked out Candorâ€™s Google questions and got asked a few of the same ones (https://candor.co/interviews/data-scientist/google)

Got my offer a few days ago, but here are some questions I got during the various rounds:

- Tell me about projects you have worked on in the past
- Follow ups on technical aspects of the projects and difficulties faced/what I learned
- A/B test questions asking what test to use, how to calculate sample sizes, power of test (pretty standard questions overall)
- SQL and Python questions
- Time series questions such as application of Bayesian time series
- Questions on linear regression focusing on assumptions for different scenarios

Check out my post for my interview timeline and experience! I DID IT! Google Product Analyst / Data Science end to end