If you have a PhD in statistics, data science, or something similar, are you pretty much golden?

I do and jobs are plentiful. Decided I wanted to go the professor route vs 50hr work weeks though. Summer research can be conducted anywhere.

Not really golden -- more like gold-plated. But most people can't tell the difference, so it's OK.

Was at a major tech conference in the midwest and saw a renowned data science speaker who used the term "Liberal Arts Refugee" to describe himself and others in his field which is somewhat accurate. By contrast, at another major tech conference on the west coast I witnessed a guy talk about how data science is something Software Engineers, DevOps, Programmer Analysts and DBAs have done since the 1990s as part of their jobs w/o some trendy label while an echo of mocking laughter erupted in the room.

Do I think the field makes you "golden"? I think it may enhance your career trajectory into the tech world if you are struggling to gain experience that best suits your ability. The M.S. in Data Science is better than a $15k code academy and acts as a polishing to your resume. However, I think a Master's in Computer Science will hold more weight out of the gates than a Master's in Data Science. At some of the more renowned institutions hopping on the Data Science bandwagon since 2015 you will find that the program will live in the statistics department and sometimes statistics lives in Math or is shared with Computer Science. Overall, the non-medical PhD is more an expression of passion for academia and indicates most of the time that you intend to return to academia in some capacity. The typical master's programs usually have two paths: fastrack professional route or the other route toward the PhD.

The other poster said a resume "plated" or gilded with gold and gilded reminds me of Mark Twain's Gilded Age quotes. The Gilded Age looked glittery on the surface but the glitter masked social problems. Moreover, I think platinum is worth more than gold. A PhD in Computer Science, Math or Engineering (EE, CE, ME) are platinum. A Master's in Data Science is gilded and the person who teaches them has the PhD in Data Science or some other respective discipline on or near its position on the academic spectrum (statistics, computer science, math, etc.).

Depends on whether you have what it takes to be productive. I've worked with PhD holders who were worthless and had to be terminated for incompetence. The degree shows you have aptitude, the actual job shows if you can actually cut it when it counts.

babbler guy wrote:

By contrast, at another major tech conference on the west coast I witnessed a guy talk about how data science is something Software Engineers, DevOps, Programmer Analysts and DBAs have done since the 1990s as part of their jobs w/o some trendy label while an echo of mocking laughter erupted in the room.

Then you (and the speaker) don't really know what data science is. I've got an MS in numerical modeling/stats and have worked in all aspects of data management in various industries and healthcare for 25 years. (Currently working in healthcare analytics.) I've rarely encountered a programmer or DBA that understands stats and data analysis well enough to show even mediocre competency as a data scientist. I would rather hire an MS in data science/stats and teach them to code than try to teach a programmer how to do stats.

To the OP: A PhD in data science? Waste of time. Get a lower degree and get working ASAP.

This.

I worked full time for 10 years before I started an MS in Data Science. The MS took me 5.5 years to finish with a full thesis while working full time.

Physics major in undergrad. When I first started working I learned Excel and Access first. Then I got into SQL Server. Then I learned programming in VBA and did a lot more complicated stuff with Excel and Access. At one point I was almost doing SQL Server DBA work but I got into doing analysis in Excel. Things like simple linear regressions and building complicated reports via pivot table. Did some more complicated things in SPSS like survey design and response. This was all before starting my MS.

My point is that before I started the MS I had substantial experience working with data and working with different software packages that did "stuff" with data. I knew SQL like the back of my hand, knew how to work with CSVs, BCP data, looping. Things that sound simple but if you're seeing them in an MS program for the first time can be really hard to get. The kids who washed out were the ones who had no experience working with data before and couldn't keep up.

I see that in my professional life now. I've worked with several PhD Data Scientists (mostly math PhDs) who couldn't do anything. They couldn't work with data, they didn't understand building data structures, they couldn't handle the ambiguity of most real projects. They expected to show up and have someone hand them a data set with all the variables nicely coded and a nice target made for them. In the real world it doesn't work like that. It's usually; here is a vague problem we're trying to solve and here is our entire data warehouse...go. Those guys didn't last long. They either couldn't or wouldn't learn the dirty parts of the job.

Anyway, I also agree with the poster who mentioned Data Science is just a trendy job title. I don't agree that your average DBA or software guy was doing that type of work. The guys doing Data Science stuff back in the day were just Data Analysts, Analysts, Statistical Analysts, etc.

This. 1 million times this.