When I started my undergraduate science career, I was under the assumption that the only "real" careers for graduating students were in academia. That misunderstanding followed me through graduate school, where it only became clear rather close to my defence that perhaps I didn't want or need to continue on the path to becoming an academic.

To jump to the end of the story, I am now a partner at Scimatic Software, where we write software for scientists. That means everything from data analysis, user interfaces, embedded programming, and the occasional blog post or web article. The problems that we're working on are of interest to scientists, and our goal is to help as many scientists as we can.

Jim Graham of Scimatic, Toronto.

Our work is currently split between contract work for our clients, most of whom are laboratory-oriented hardware manufacturers, and work on our own software products. For our clients, we can work on nearly all of the software necessary to run an instrument, get the data, and then do analysis. For example, we might work on embedded controls for a surface plasmon resonance (SPR) instrument, and then the control software that drives the device from a PC, and finally the analysis software for data processing. For that last software package, I've been working on chemical rate equation modeling through numerical integration of ODEs. For our product work, we are building applications to help scientists organize their labwork more efficiently.

So, how did I get here, and is anything I learned useful for current students in mathematics or the sciences right now?

Although I took a circuitous route and 10+ years to get here, I think there are a few general lessons that can be drawn from my experiences. First, there is a need for people with math and science training outside of academia. Second, the resources to get you that job aren't discussed that often within academia.

I strongly believe that we need to have people with science and mathematics training in the general workforce, not just within the ivory tower of academia. The first reason is one of practicality; there are not enough academic jobs to support everyone who gets a Master's or Ph.D, and we are not likely to see an immediate reduction from admitting committees to "right-size" the flow of incoming students. Furthermore, I'm not sure that we would want to; lots of great research is done by Master's and Ph.D. students who don't want to continue on in academia. We may have to reduce the size of incoming classes of graduate students due to funding pressures, but I don't think we should do so because there isn't a professorship waiting for every student at the end of the line. Having said that, I do think it's necessary to inform every incoming student what the odds of getting that professorship are, so that they can make an informed decision about whether they want to continue. Pointing out what their options are upfront will help them make an informed choice.

The second reason has more to do with the society that we should want to be building. In the current economic climate in the United States, (maybe to a lesser degree elsewhere), we continually hear that we need to have highly-skilled workers who will drive innovation. That's contrasted to the political climate where being downright hostility to science can score big points. I think it's necessary that we encourage anyone who wants to study science and math to do so, and help them find the right employment that utilizes their skills after they finish their education. Having that educated workforce will help drive innovation, but also counter some of the obvious anti-science politicking that goes on.

When I left graduate school ten years ago, the biggest non-academic employment opportunities for science and math students coming out of graduate school was working for a bank, mostly in "quantitative analysis" (being a "quant") for a trader. I'd say that about 40% of my fellow students who did not continue in academia chose this route. The remainder became management consultants, or computer programmers.

That was the route I followed after graduate school. I joined a tech startup that wasn't focussed on any scientific problems. In the current climate, programming jobs are relatively easy to come by. However, even though I used many skills I had learned in graduate school, I felt that something was missing -- I wanted to leverage not only the skills I'd learned in graduate school, but also the science itself. After that, I was lucky enough to "network" at an open-science conference where I met the founder of Scimatic, and realized that one can have a job and a career working on science-related topics without being in academia.

Not to downplay "quants" or management consultants, but there's a much bigger world out there, and it behoves any student in graduate school to explore it. So, where are the jobs?

• Caltech astro-physicist Sean Carroll writes at "Cosmic Variance". He wrote a series of blog posts covering non-academic careers, and summarized those posts here.
• PhDs.org has a career resources page "... for scientists and would-be scientists at all levels, from high school students through Nobel laureates."
• SIAM created a report on Mathematics in Industry.
• Mark Chu-Carroll wrote a similar "how I got here" post on how he ended up at Google.
• Since I mentioned politics, we should probably be looking to produce scientists who can talk to and work with politicians. Sheril Kirshenbaum has a list of resources for those who might want to work in policy or government at Policy Fellowships For Scientists & Engineers.

My personal anecdotes run throughout this article, and we all know that the plural of "anecdote" isn't data. However, I do believe that it is possible to have a good science-focussed career outside of academia; a career that's stimulating and personally rewarding, as well as financially stable. I hope that anyone who is considering graduate school in science or math takes away two ideas; first, the end goal of graduate school doesn't have to be life as an academic, and second, that there are jobs and careers out there that leverage the knowledge gained in graduate school.

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Jim Graham is a partner at Scimatic Software. He has been developing software for 10 years. Prior to joining Scimatic, he worked in a variety of programming languages developing a compiler build engine for a Chicago-based start-up.

Jim holds a Ph.D in experimental particle physics from the University of Chicago. His work on the KTeV experiment at Fermilab is where he gained his expertise in readout electronics and software, statistical analysis software and Monte Carlo simulations.