Following the links on the program at the Georgia Tech Web site, the program looks like a fairly wide buffet from practical computing, current business applications, statistics, and operations research.

Georgia Tech is especially strong in operations research.

So, here data science is a new bottle of wine blended from some now quite well known old bottles of wine. And it is not nearly the first such blending since there have also been programs such as mathematical sciences and applied mathematics. Other blendings have included mathematical finance, financial engineering, and bio-statistics.

Apparently the high current interest is because now the associated computing is much cheaper, more powerful, and easier to use. And there has been a lot of hype from some sources.

However, I question if US mainline business is much interested: IMHO and my experience says that nearly any specialized technical material faces a serious obstacle since in the organization chart the highest ranking technical person (if not the CEO then necessarily a subordinate) has to report to a supervisor who knows from much less to nearly nothing about what that technical subordinate person is doing.

MD doctors, CPA accountants, licensed engineers, and licensed lawyers have some crucial, serious professional status, processes, support, etc. that is missing with applied mathematicians, statisticians, data scientists, etc.

For software developers, roughly, the solution is for the organization to have a CIO, all the developers are in the CIO's organization so report only to experienced developers, and only the CIO reports to, interfaces with, non-experts in computing.

Computing is now so darned important that the rest of the C-suite has to swallow their pride and accept the CIO at the table.

Net, I fear that data scientists will have too little professional or organizational protection from rain falling down the organization chart from the C-suite.

Or, for the supervisor, most projects will be lose-lose: If the project fails, then the supervisor has a black mark from wasting money on a failed project. So, with a failed project, the supervisor loses.

If the project is successful, then the supervisor and, maybe, everyone in the C-suite, maybe even including the CEO, can be afraid of the project leader now regarded as a 900 pound tiger and, thus, a loss for the C-suite.

Here the organization chart from the project leader up to the CEO is engaging in classic goal subordination, that is, pursuing what is best for themselves personally while sacrificing what is good for the company.

And for startups, what fraction of venture partners would be able to evaluate a proposal that makes heavy use of some of the more advanced applied math in that Georgia Tech program? Net, the venture partners don't know the technical material, either.

Or, as I suggested, nearly all wine in the blend is now quite old, and it didn't achieve much traction in mainline business.

My short summary view is that for such technical material, especially material more advanced than in the Georgia Tech program, and for a startup, the founder CEO needs to be both (A) the main expert in the technical material and (B) essentially a solo founder who can write the software, bring it to market, and get the coveted traction significantly high and growing rapidly -- at which time the founder may not be willing to accept equity funding and report to a BoD that does not understand the work, that is, be back in the situation of a technical subordinate reporting to a supervisor who does not understand the technical work and, with the low expenses of a one person company, just grow organically from revenue.

Or, IMHO, the most promising career future of an applied mathematician, etc., in business is to be a solo founder of a startup.