"Every business collects data, and it's the job of the data scientist to analyze, interpret, and communicate that information in a way that will help drive company decisions. In an interview, expect to answer technical questions about your ability to perform quantitative tests as well as create clear visualizations of large, complex data sets. Come ready to discuss past projects you've worked on and how you communicate data findings clearly and concisely in order to help solve business-related problems."
You are compiling a report for user content uploaded every month and notice a spike in uploads in October. In particular, a spike in picture uploads. What might you think is the cause of this, and how would you test it?
Hypothesis: the photos are Halloween pictures. Test: look at upload trends in countries that do not observe Halloween as a sort of counter-factual analysis.
We cannot say what has caused the spike since causal relationship cannot be established with observed data. But we can compare the averages of all the months by performing a hypothesis testing and rejecting the null hypothesis if the F1 score is significant.
The photos are definitely Halloween pictures. Segment by country and date and check for a continual rise in photo uploads leading up to October 31st and a few days after for the lag. There's also a ton of these product questions like this on InterviewQuery.com for data scientists