If you love doing empirical work, you've probably wondered what it's like to work at an organization such as Google, where the term "Big Data" takes on a whole new meaning.
If so, you'll enjoy reading Jeff Leek's "Interview with Nick Chamandy, statistician at Google", on the Simply Statistics blog. Nick provides some interesting insights into the life of the statisticians/data analysts at Google, and the culture surrounding their work.
Here are a few excerpts:
"When posting job opportunities, we are cognizant that people from different academic fields tend to use different language, and we don’t want to miss out on a great candidate because he or she comes from a non-statistics background and doesn’t search for the right keyword. On my team alone, we have had successful “statisticians” with degrees in statistics, electrical engineering, econometrics, mathematics, computer science, and even physics. All are passionate about data and about tackling challenging inference problems." ..................................
"Our data sets contain billions of observations before any aggregation is done. Even after aggregating down to a more manageable size, they can easily consist of 10s of millions of rows, and on the order of 100s of columns." ......................
"In the vast majority of cases, the statistician pulls his or her own data — this is an important part of the Google statistician culture. It is not purely a question of self-sufficiency. There is a strong belief that without becoming intimate with the raw data structure, and the many considerations involved in filtering, cleaning, and aggregating the data, the statistician can never truly hope to have a complete understanding of the data." .........................
I definitely approve of that philosophy.
© 2013, David E. Giles