Moving from Academia into industry
14 June 2015

In mid-April, I participated in a roundtable about non-academic careers for political scientists at the Midwest Political Science Association annual conference in Chicago. I kept it simple and tried to just tell my experience when I decided to not follow the usual path towards a tenure track position. In a field with so little tradition (and awareness) about non-academic jobs, transitioning to industry sometimes feels like a leap in the dark.

Ever since then, I have tried to collect the main points I tried to touch during my presentation. Better late than never.

  1. ``Talking about non-academic jobs makes as much sense as talking about non-elephant animals.’’ The very name of the panel captures an academic prejudice. There is no such thing as a non-academic job and it is counter-productive to try to summarize the world outside academic departments that way. There is a wild heterogeneity of positions in industry and they all require very different skills. Just because you do not want to teach or write papers for a living, it does not mean that you are stepping outside the path you are expected to follow. The way I see it, a PhD is a degree that prepares you to do research, and Academia is just one way to take advantage of that training. I do not understand why we are still trying to describe industry in the negative.

  2. Academia is not the only place where you can feel intellectually motivated. It is true that research in industry and in academic departments —specially in the social sciences— focus on very different topics. However, my own job is very much research-oriented. What I get every morning is an analytical problem that needs be solved, exactly the same way it was when I was doing my PhD. The main difference with respect to academic research is that the solutions I propose have to be reached much faster and they have to be actionable —conclusions have to guide practical decisions with real consequences. That means that breadth of the areas that I tackle is considerably larger, and also that success is measured in very different units.

  3. No one cares that much about your PhD. You will meet lots of people, possibly smarter than you, who have chosen not to spend several years writing a dissertation. There is a positive counterpart to it: except for very exceptional cases in which your dissertation has a direct applicability to the company, your research topic does not matter. A PhD signals that you are good at research and that is a skill that is very difficult to acquire. If anything, a company will be interested in your abilities as a researcher and not as a world-class specialist in your very small topic of interest. Therefore, do not worry that much about your dissertation being on something unrelated to the sector you are moving too. Also, if anyone ever asks you about your dissertation during a job interview, they are probably more interested in how you did it than in what you wrote about.

  4. Learn tools while you are in graduate school. You want your toolkit to be as large as possible to not limit yourself when you are facing applied problems. But be smart about your investment and try to learn tools in the way that will be useful. People will be positively surprised if you know how to code, but it would be really strange if you suddenly wanted to become a software developer if you did you PhD in political science. That said, statistics and microeconomics/game theory are probably the most useful classes I have ever taken, and I regret every day not having taken even more classes in maths (a bit of measure theory never hurts) and computer science.

  5. The main stigma of academics is that they are ineffectual, that they have a hard time accepting the “good enough” solution —the approximate solution that can be reached in the short term. Alas, my experience is that it is true. I have participated in bizarre discussions in which someone would outline a project that would take months to complete and that would only marginally improve a method that could be deployed in one week. On the positive side, it means that you have developed a good eye for detecting flaws in a structure and that puts you in an excellent position to come up solutions that can be extended and improved over time. Just do not get caught up in the beauty of question, and know how to provide different feasible solutions for different expected timelines.