As some readers of this blog will have already heard, I left my position at Oklahoma State this summer to become a software engineer in Google’s Cambridge/Boston office. My decision to leave academia for the private sector (aka the Dark Side, as certain mathematicians who I won’t name like to call it) was the result of a number of years of soul-searching, research, toe-dipping, etc. In this post, I want to share my experiences for the sake of any young Ph.D.s or current graduate students who are grappling with this same decision. (Disclaimer: The views expressed below are my own and were not endorsed or approved by my employer.) I’ll focus on software-related jobs, since that’s what I know about, though most jobs for mathematicians these days will probably involve a fair amount of programming anyway. (Also, here’s some additional required reading for anyone finishing up a Ph.D.: The Fame Trap.)
For the record: When I was in graduate school, I had no intentions of doing anything but becoming a math professor. Things didn’t change during my postdoc either. In fact, even in the spring of 2009, as the financial crisis was eviscerating the job market and unemployment was staring me grimly in the face (until Bus Jaco somehow convinced the right people to let me fill the vacancy created when Joseph Maher left OSU, but that’s another story…) my last-minute applications were all for one-year visiting lecturer positions.
At the time, my assessment of the private sector vs. academia was pretty bleak: Your salary is higher, but the price you pay for that is longer hours at a mind-numbing job with a micro-managing boss. But it turns out, things aren’t actually that extreme. In fact, there are a lot of nice things about the private sector, that make the comparison much more subtle, even if you take money completely out of the picture.
First, lets talk about working hours: Many youngsters (and non-academics) point to the flexible schedules and long holidays as one of the perks of academia. But by the time you make it into the ranks of the tenure-track, it becomes clear that the flexibility just means that you get to pick which 60 (80?) hours a week that you work. And vacations are the times when you get to work on your real work (research) or else feel guilty for not doing all the writing that you didn’t get done during the semester.
In the private sector, on the other hand, policies regarding time vary quite a bit. I’ve heard that there are some jobs where you’re expected to be in the office 12 hours a day, whether or not you have anything to do. But there are many more companies (including Google and most of its peers) that value work-life balance and have policies that explicitly try to discourage their employees from working harder than is healthy for them. They don’t just do this because they’re nice people – they do it because they want to prevent burn-out, which in the long run counteracts any extra productivity that would come from an 80-hour week. (Don’t believe me? There are books about this.) I spend around 40 hours a week in the office and almost never bring work home. Some of my new colleagues work longer hours than that, but overall I think the attitude towards work/life balance is much healthier.
So this brings up an interesting point: As great as it is to be completely in charge of your own day-to-day and longer-term activities, there are actually some benefits to having a manager who is aware of and has a stake in your daily work: Namely, they can take a more objective view of what you’re doing and help to make corrections, such as pushing back against your self-applied pressure to work harder than is healthy. Granted, not all managers will do this, but if you find the right job at a good company, they likely will. (Google makes all managers go through training on this sort of thing, and I expect there are similar policies at many other companies.)
Next, about the “mind numbing” work: No, the work that I do is not as deep or as beautiful as the mathematics that I previously got to learn and think about. It doesn’t require the sorts of insights that come to you surprisingly at random times, and double you’re pulse rate even though you haven’t moved. It doesn’t require thinking about a problem during every spare moment for days or weeks or months. But it is quite interesting, and exercises most of the mental muscles that one works so hard to develop in a math graduate program.
In particular, it turns out that (at least in my experience) writing a computer program is a lot like writing a math paper, or a proof: You start with an overview of the thing that you want to produce, at a high-level of abstraction. Then you break it up into smaller pieces, and work out the details of each piece at a low-level of abstraction. Then you start putting these pieces together, slowly working from lower levels of abstraction to higher levels. Sometimes, you realize that they don’t fit exactly right, so you have to drop down to a lower level of abstraction to change some of the components before working your way back up.
It turns out that the ability to switch between different levels of abstraction like this is highly prized and relatively rare, even though it’s sometimes taken for granted in academia. It’s basically the same skill that you need to read and write proofs in mathematics (which is the reason I believe that math majors/Ph.D.s can make better software engineers than computer science students. But don’t tell anyone I said that…) Programming is basically this process with some syntax (which is the easy part) layered on top.
In mathematics research, the fun part is coming up with the ideas and the painful part is organizing them into a paper. In software engineering, coming up with the ideas that will solve a given problem (or determining that it can’t be solved) is usually pretty straight forward, if not trivial, by putting together ideas that have already been worked out by others. But implementing them (i.e. writing source code) is quite interesting, and significantly less painful (at least in my experience) than writing papers. Getting the pieces of a computer program to fit together tends to take a lot more time, even for very simple systems, because you can’t gloss over the details as much as you do in a math paper, but it also makes it more interesting.
So the difference between a mathematics research project and developing a complex piece of software is (again) a trade-off. For me, it comes down to how much you enjoy grappling with nearly unsolvable problems, versus how much you dislike writing papers. (And if you actually like writing papers, then lucky you…) There’s also something to be said for being able to know, at the outset of a project, that there is a solution and roughly how long it will take to finish it.
And, of course, in the private sector you generally don’t get to teach. For some this may be a drawback, and for others, maybe not. For me it was yet another trade-off – there were a lot of things I liked about teaching, and other things I didn’t. One thing I didn’t like was the constant tension between time/energy spent on teaching vs. research.
Finally, no discussion of an academic career would be complete without a discussion of committees. I actually enjoyed much of the time I spent in committee meetings discussing important questions about how the department should be run. These were usually questions that needed to be made, and required the sort of experience and insights that could only come from faculty members. Sometimes we spent more time than we needed to splitting hairs, or discussing issues that didn’t deserve the amount of time we devoted to them. But overall, I think most of the committees I had a chance to experience served an important purpose.
At the same time, they required a lot of time, and that time increases every year, as you lose the protections designed to give pre-tenure faculty time for research. So it’s not uncommon, as your academic career progresses, for research (which for me was one of the main draws of an academic career) to become a smaller and smaller part of your day-to-day activities.
In the private sector, on the other hand, decisions tend to get made more quickly and with less discussion. I have very few meetings at Google, and most last less than half an hour. Other people (such as managers) spend much more time in meetings than I do, but they work hard to keep them short and to the point. In general, a lot of the types of decisions that are left to faculty in academia are delegated to specialists or managers in the private sector. This obviously has both benefits (in terms of time) as well as drawbacks (in terms of control.)
So, that should give you a rough idea of the factors I considered when I decided to leave academia. I want to stress that these are all trade-offs, and how you weigh them is a personal decision. There are many mathematicians who would be happier in academia, but there are also many who would do better in the private sector.
While it may be scary to think of all the bright young minds that academia could lose to the private sector, my experience suggests that there were won’t be a shortage among the mathematicians who stay. In fact, I would argue that having such a high ratio of job seekers to jobs is much worse for the morale of the field, makes it easier for administrators to replace tenure lines with contingent faculty positions, and ends up forcing many promising young mathematicians to leave against their will anyway. If more recent Ph.D.s choose to go into the private sector, then the ones who stay will tend to be the ones who are particularly devoted to teaching (on top of their excellent research programs) which is what our universities need. Having the remaining math Ph.D.s go out into the world (willingly) and show how capable they are will both help justify the NSF grants that contributed to their education and encourage more students to enter math graduate programs, or become math majors.
When I was a graduate student, I didn’t take an objective look at the option of entering the private sector, and I don’t think many of my peers did either. But my impression is that attitudes about this are starting to change, both among students and faculty. I hope that in the future, every young mathematician will give serious thought to both options, and will be able to make a well informed decision.