| 1. My work consumes most of my time and energy - how would one find time to work on side projects and build a portfolio, when the academic workload is so all-consuming Turn off the TV, close Ph.D. comics stop procrastinating. That's a fairly glib and slightly offensive answer, but it's the best I've got. There are no shortcuts. Getting yourself ready to work in industry will take time and effort. I can, however, suggest that adopting a more rigid industry-style work schedule can help. In grad school, my time management skills sucked, and I'm pretty sure I wasn't alone in that. One thing you can sometimes do to speed things up is to take pieces of your research and turn it into side projects. For instance, something I didn't do (but should have) was properly package/test my numpy shared memory library. 2. I felt like I had to apply for industry jobs in my niche, otherwise I would be competing against a much larger pool of general engineers/science graduates. You overestimate the number of general engineers who are capable of quantitative work. When I said there is value being the guy in the room who understands regression and confidence intervals, I meant it. The much larger pool of general engineers/scientists is the target audience of blog posts like this one: http://www.zedshaw.com/essays/programmer_stats.html Do things like Naive Bayes, SVMs and Black Scholes seem straightforward to you? If so, you are a quant. Now you just need to become a developer. |
I'd just like to second that. If you've learned enough math to be an expert in a scientific niche, you're almost certainly miles ahead of most developers you'll work with.