Gary Ruiz writes:
I am a first-year math major at the Los Angeles City College in California, and my long-term educational plans involve acquiring at least one graduate degree in applied math or statistics.
I’m writing to ask whether you would offer any career advice to someone interested in future professional work in statistics.
I would mainly like to know:
– What sort of skills does this subject demand and reward, more specifically than the requisite/general mathematical abilities?
– What are some challenges someone is likely to face that are unique to studying statistics? Any quirks to the profession at a higher (mainly at the research) level?
– How does statistics contrast with related majors like Applied Mathematics in terms of the requisite training or later subjects of study?
– Are there any big (or at least common) misconceptions regarding what statistical research work involves?
– What are some of the other non-academic considerations I might want to keep in mind? For example, what are other statisticians usually like (if there’s a “general type”)? How does being a statistician affect your day-to-day life (in terms of the time investment, etc.), if at all?
– If you could give your younger self any career-related advice, what would it be? (I hope this question isn’t too cliche, but I figured it was worth asking).
– Finally, what are the most important factors that any potential statistician should consider before committing to the field?
– Programming is as important as math. Beyond that, you could get a sense of what skills could be useful by looking at our forthcoming book, Regression and Other Stories, or by working through the Stan case studies.
– I don’t know that there are any challenges that are unique to studying statistics. Compared to other academic professions, I think statistics is less competitive, maybe because there are so many alternatives to academia involving work in government and industry.
– I don’t know enough about undergraduate programs to compare statistics to applied math. My general impression is that the two fields are similar.
– I don’t know of any major misconceptions regarding statistical research work. The only thing I can think of offhand is that in our PhD students we sometimes get pure math students who want to go into finance, I think in part because they think this will be a way for them to keep doing math. But then when they get jobs in finance, they find themselves running logistic regressions all day. So it might’ve been more useful for them to have studied applied statistics rather than learning proofs of the Strong Law of Large Numbers. But this won’t arise at the undergraduate level. I’m pretty sure that any math you learn as an undergrad will come in handy later.
– Regarding non-academic considerations: how your day-to-day life goes depends on the job. I’ve found lawyers and journalists to be on irregular schedules: either they’re in an immense hurry and are bugging me at all hours, or they’re on another assignment and they don’t bother responding to inquiries. Statistics is a form of engineering, and I think the job is more time-averaged. Even when there’s urgency (for example, when responding to a lawyer or journalist), everything takes a few hours. It’s typically impossible to do a rush job—and, even if you could, you’re better off checking your answer a few times to make sure you know what you’re doing. You’ll be making lots of mistakes in your career anyway, so it’s best to avoid putting yourself in a situation where you’re almost sure to mess up.
– Career advice to my younger self? I don’t know that this is so relevant, given how times have changed so much in the past 40 years. My advice is when choosing what to do, look at older people who are similar to you in some way and have made different choices. One reason I decided to go into research, many years ago, was that the older people I observed who were doing research seemed happy in their jobs—even the ones who were doing boring research seemed to like it—while the ones doing other sorts of jobs, even those that might sound fun or glamorous, seemed more likely to have burned out. Looking back over the years, I’ve had some pretty good ideas that might’ve made me a ton of money, but I’ve been fortunate enough to be paid enough to have no qualms about giving these ideas away for free.
– What factors should be considered by a potential statistician? I dunno, maybe think hard about what applications you’d like to work on. Typically you’ll have one or maybe two applications you’re an expert on. So choose something that seems interesting or important to you.