How would you differentiate the roles of statistician, data scientist, and data engineer? I've used and heard the titles "statistician" and "data scientist" used interchangeably, and the Wikipedia entry for data science [1] gives evidence to support that usage since the late 90s:

"In November 1997, C.F. Jeff Wu gave the inaugural lecture entitled "Statistics = Data Science?" for his appointment to the H. C. Carver Professorship at the University of Michigan. In this lecture, he characterized statistical work as a trilogy of data collection, data modeling and analysis, and decision making. In his conclusion, he initiated the modern, non-computer science, usage of the term "data science" and advocated that statistics be renamed data science and statisticians data scientists."

From the same article, a quote from Nate Silver:

"I think data-scientist is a sexed up term for a statistician....Statistics is a branch of science. Data scientist is slightly redundant in some way and people shouldn’t berate the term statistician."

If your skillset differs from a statistician, then calling yourself a data scientist is not going to be a differentiating title in common parlance.

[1] https://en.wikipedia.org/wiki/Data_science#History

I think the quote and definition from the blog is a good one: “better engineers than statisticians and better statisticians than engineers”. Perhaps that 1997 quote was influential in the decision to use the term Data Science, I think the current usage encompasses much more than statistics. When I started it required the ability to push production code, build statistical models, and communicate results effectively. Maybe I'm wrong and maybe the tools got better, but for a while, you couldn't provide value if you couldn't get to the data or create the data you needed.