A friend of mine sent these two articles and asked for my comments on them.
The first article talks about how valuable PhDs, postdocs, and PhD candidates are to management consulting firms. It goes into detail about the training that a lot of PhDs receive while working towards their degree, and that their training is just as valuable as what MBA’s receive.
Now, it all sounds nice on paper, but my experience has been the polar opposite. I applied to several consulting firms last year and was either soundly rejected or received no response (which is quite common when applying for jobs online), and this is in spite of being one of those “[valuable] Science-PhD holders” the author talks about. So I really have no idea what management consulting firms are looking for.
The author also states:
“The broad set of valuable transferable skills that you developed while in graduate school go largely unrecognized and unarticulated within the academy. Most PhD graduates restrict their job searches to what they feel qualified to do, rather than exploring what they are capable of doing.”
Again, this trope sounds nice on paper, but my experience with applying for jobs has been quite the opposite. The whole idea of “transferable skills” only really holds in the tech industry, and that too for a small set of subjects (more on this in a moment).
The second article mentions that early-stage scientists (such as assistant professors, post-doctoral fellows, and PhD students) should also look into commercializing their successful ideas and forming start-up companies. This is solid advice. The article also mentions that professors are also not the best people to be running start-up companies, due to the many demands on their time. That is better left to younger people. Of course, this comes with a caveat.
Applied sciences, engineering, and computer science are by their nature easier to commercialize, as opposed to theoretical or more “pure” fields. Problems that are academically interesting are not necessarily ones that will lend themselves to commercialization once investigated. Another issue is that startups are rarely founded off of PhD research because the interests of the advisor and the student are opposed at that point. The advisor will want the successful student to continue working, generating results and writing papers, while the student will want to leave to start the company. In any case, as the author mentions, it never hurts to allow PhD students opportunities to network with successful people in their field; this will help later when they apply for jobs! Sadly, most schools do a piss-poor job in this regard. In most universities, PhD career services are virtually nonexistent, as are networking events for graduate students.
In any case, back to the subject of transferable skills. From what I have seen, transferable skills are those secondary skills that you might pick up on the course of your degree that are not necessary for success in that field, but can be used somewhere else. For example, most PhD holders would have given talks at conferences at some point. Based on that, “making and giving presentations” can be listed as a skill, even though this something that no self-respecting person would be caught putting on his or her resume. This skill is transferable to other fields where giving presentations is important, such as consulting. I’m not sure if this is a good example or not, but it is what I could think of.
Now, one transferable skill that is being thrown around a lot lately is “data analysis”. The author even refers to it in the first article I linked to above:
“If you have earned a PhD, you know, for example, how to analyse data. You also understand how to examine those results to gain insights.”
The term “data analysis” is beginning to seriously annoy me, because it is incredibly vague. A five-year-old putting his hand on a hot stove, screaming in pain, and then learning not to touch the stove again is doing data analysis! Yet would people call the five-year-old a “data scientist”? Even if others wouldn’t, I would – the kid has used evidence (even if it is a single datum) to draw a conclusion! So yes, in the broad sense, we are all “data scientists” and we all go about our day doing “data analysis” all the time, even if we do it unknowingly!
But the crux of the matter is that the type of data you will encounter varies from field to field, and the types of conclusions you can draw – the analysis, in other words – is domain-specific. In other words, “data analysis” is not a transferable skill. This is a seemingly simple fact that unfortunately is being overlooked by recruiters, employers, and tech workers. For example, I can readily interpret NMR spectra, GC-MS data, and other types of spectra that are commonly encountered in a chemistry lab. However, I would be laughed at if I claimed to be doing “data analysis” in the sense that is used in the tech industry today! What the tech industry calls “data science” or “data analysis” is the statistical interpretation, most often using methods derived from computer science, of large sets of facts or figures that have been compiled. Case in point: Thanks to a friend, I got an interview a few days ago for a “data analytics” position. The HR recruiter who called me was thoroughly confused by my resume, and I had to clarify that even though I had a PhD in science, I had zero skills that they were looking for. She told me “oh yea, we regularly hire people from a variety of backgrounds for this position…we have computer scientists, math majors, statisticians, and even physicists!”. Now, as far as transferable skills go, they probably have a very good command over computer science and programming, as well as a strong mathematics background. These skills are not generalizable to all scientists (just like how I would not expect a PhD computer scientist or statistician to be able to go into a chemistry lab and synthesize small molecules)!
As one of my friends told me,”…well, looks like you have a PhD in an inferior science”.