Should I go to grad school for a stats PhD, change jobs, or…?
April 5, 2013 12:48 PM Subscribe
Feeling a little stuck in my current job; unsure if I should go for the PhD or cross it off my list and change jobs.
(Warning: brain dump.)
So, uh, I'm 24, and it's been almost two years since I graduated with an applied math degree. I've been working at a medical school in the Bay Area (hint: it's the one in the city) since then as a statistician, and now as a senior statistician. Basically, what that entails is working with about 10-15 professors/PIs on hammering out the methodology for their projects, writing loads of R and Python code, writing papers, giving talks/tutorials, and mentoring. I've taken on and turned around some pretty hairy projects, and led teams of 2-3 other statisticians/analysts, some with substantially more experience with me.
Anyway, it's a great job and it's hard for me to imagine having the flexibility and work-life balance that I have now anywhere else. However, I've been feeling a little weird about my situation lately, like I should be either committing to going to grad school for a stats PhD or crossing that off of my list entirely. The thing is, I'm not too hot on the traditional biostats stuff, plus I couldn't prove my way out of a wet paper bag in undergrad, so I'm not sure I would enjoy going through that experience again in grad school. I don't think I was able to prove anything non-trivial in any of my undergrad math courses. What I'm kind of afraid of, though, is that maybe, say, 20 years from now, I'm going to go and say to myself, gee, maybe I should've gotten that PhD back when I had the chance. I don't know how true that is, given that I'm pretty sure I don't want to end up in academia.
What I am interested in, though, is writing code, playing with data, and the machine learning side of things. I feel more like I want to make things that other people can *use*, as opposed to producing insights that they can act on. I think I would be at home in a more data science-ish role, or even as a software engineer. I've worked with my teams to get get all our code under source control and use best practices; I know my algorithms and data structures, and I have the (somewhat) perverse hobby of playing with the Linux kernel in my spare time. I like figuring out how stuff works, pretty much. Having said that, if I *do* cross grad school off of my list, I'm not sure how much longer I could stick around in my job, even with another promotion coming up. I feel kind of like I'm in a bubble, and that I'm pretty much reaching the limits of how much I can grow here.
I've been to tech meetups/networking events and whenever the topic of my background comes up, the kinda responses I get are like, oh, my (software) company really loves statisticians, you should check us out! Or it's "APPLY TO GOOGLE!!!" That kind of stuff. While I can tell there's a lot of interest out there for people like me who are good at stats and with data in general, and who can also code/wear the engineer hat, I'm kind of clueless as to how to get in touch with, or even find out about, places that'd be the right fit for me. Right now it's just Google on my radar -- from what I've heard/read about, it's kind of the model of a place I'd like to work (although not necessarily optimal, probably) because of the intersection of 1) lots of data, 2) interesting questions, 3) interesting systems/methods and 4) an engineering-first culture (for the most part) with lots of smart people around. Where else should I be looking?
In the same vein, I think I'd like to get into consulting/freelancing, but then again, I don't really have any idea how to begin doing that either.
Anyway, with all that out there, I think I'm feeling pretty sure that I wouldn't be a good fit for grad schools; what's open is just how much the lack of a PhD would hold me back later in my career, given what I want to do. So -- what's the best way to go about finding out about opportunities that are better fits for me than what I have now? Right now, I'm not really in a rush, but it sure would be nice to have a roadmap.
(Warning: brain dump.)
So, uh, I'm 24, and it's been almost two years since I graduated with an applied math degree. I've been working at a medical school in the Bay Area (hint: it's the one in the city) since then as a statistician, and now as a senior statistician. Basically, what that entails is working with about 10-15 professors/PIs on hammering out the methodology for their projects, writing loads of R and Python code, writing papers, giving talks/tutorials, and mentoring. I've taken on and turned around some pretty hairy projects, and led teams of 2-3 other statisticians/analysts, some with substantially more experience with me.
Anyway, it's a great job and it's hard for me to imagine having the flexibility and work-life balance that I have now anywhere else. However, I've been feeling a little weird about my situation lately, like I should be either committing to going to grad school for a stats PhD or crossing that off of my list entirely. The thing is, I'm not too hot on the traditional biostats stuff, plus I couldn't prove my way out of a wet paper bag in undergrad, so I'm not sure I would enjoy going through that experience again in grad school. I don't think I was able to prove anything non-trivial in any of my undergrad math courses. What I'm kind of afraid of, though, is that maybe, say, 20 years from now, I'm going to go and say to myself, gee, maybe I should've gotten that PhD back when I had the chance. I don't know how true that is, given that I'm pretty sure I don't want to end up in academia.
What I am interested in, though, is writing code, playing with data, and the machine learning side of things. I feel more like I want to make things that other people can *use*, as opposed to producing insights that they can act on. I think I would be at home in a more data science-ish role, or even as a software engineer. I've worked with my teams to get get all our code under source control and use best practices; I know my algorithms and data structures, and I have the (somewhat) perverse hobby of playing with the Linux kernel in my spare time. I like figuring out how stuff works, pretty much. Having said that, if I *do* cross grad school off of my list, I'm not sure how much longer I could stick around in my job, even with another promotion coming up. I feel kind of like I'm in a bubble, and that I'm pretty much reaching the limits of how much I can grow here.
I've been to tech meetups/networking events and whenever the topic of my background comes up, the kinda responses I get are like, oh, my (software) company really loves statisticians, you should check us out! Or it's "APPLY TO GOOGLE!!!" That kind of stuff. While I can tell there's a lot of interest out there for people like me who are good at stats and with data in general, and who can also code/wear the engineer hat, I'm kind of clueless as to how to get in touch with, or even find out about, places that'd be the right fit for me. Right now it's just Google on my radar -- from what I've heard/read about, it's kind of the model of a place I'd like to work (although not necessarily optimal, probably) because of the intersection of 1) lots of data, 2) interesting questions, 3) interesting systems/methods and 4) an engineering-first culture (for the most part) with lots of smart people around. Where else should I be looking?
In the same vein, I think I'd like to get into consulting/freelancing, but then again, I don't really have any idea how to begin doing that either.
Anyway, with all that out there, I think I'm feeling pretty sure that I wouldn't be a good fit for grad schools; what's open is just how much the lack of a PhD would hold me back later in my career, given what I want to do. So -- what's the best way to go about finding out about opportunities that are better fits for me than what I have now? Right now, I'm not really in a rush, but it sure would be nice to have a roadmap.
So I am a software engineer, and I was struggling a few years ago with whether to go back for a PhD in computer science. I was very academically-minded in undergrad and I'd always kind of thought I was going to go back. Many of my co-workers had PhDs, so I started by asking them, and each and every one of them said it would be a horrible idea. Even though they all seemed to me very academically-minded people, who keep up with the literature and attend conferences and stuff, they really harped on what a bad time they had in grad school and how little it helped their career afterwords.
So that was my experience. It can be easy in academia to assume that everyone has a PhD and that it's the way to get ahead, but at least in my career I have found that it matters hardly at all.
Of course a stats PhD isn't a CS PhD but the sense that I have is that if you want to be in industry ultimately it won't be a good use of your next 5+ years. If you feel there are skills that you need for the jobs that you want, acquire them (perhaps with a part-time masters) but unless you want a professorship you are unlikely to need a PhD.
posted by goingonit at 1:04 PM on April 5, 2013 [1 favorite]
So that was my experience. It can be easy in academia to assume that everyone has a PhD and that it's the way to get ahead, but at least in my career I have found that it matters hardly at all.
Of course a stats PhD isn't a CS PhD but the sense that I have is that if you want to be in industry ultimately it won't be a good use of your next 5+ years. If you feel there are skills that you need for the jobs that you want, acquire them (perhaps with a part-time masters) but unless you want a professorship you are unlikely to need a PhD.
posted by goingonit at 1:04 PM on April 5, 2013 [1 favorite]
If you have enough doubt about whether you should go to graduate school that you're asking strangers for advice (even the top-tier strangers who hang out here), you should not.
posted by Etrigan at 1:07 PM on April 5, 2013 [2 favorites]
posted by Etrigan at 1:07 PM on April 5, 2013 [2 favorites]
You don't want to go into academia.
You don't want to do research.
You shouldn't get a PhD.
posted by MisantropicPainforest at 1:15 PM on April 5, 2013 [9 favorites]
You don't want to do research.
You shouldn't get a PhD.
posted by MisantropicPainforest at 1:15 PM on April 5, 2013 [9 favorites]
You like your job, you've indicated that you're gifted in that field, and that academics doesn't interest you per se. I'd get some more specific feedback, unless you're certain, that a further degree is REALLY required to advance where you are, but assuming that's so, pursue what everyone seems to be telling you and branch into IT/programming/etc.
My admittedly very general 30,000-foot view of academic hard math skilz vs. coding skills is that the latter is more rare and valuable these days, counter-intuitive as that may seem. And in IT, they don't care nearly as much what your degrees are; what counts is what you can do.
On preview, also what Etrigan said. And Misantrophic Painforest.
posted by randomkeystrike at 1:16 PM on April 5, 2013
My admittedly very general 30,000-foot view of academic hard math skilz vs. coding skills is that the latter is more rare and valuable these days, counter-intuitive as that may seem. And in IT, they don't care nearly as much what your degrees are; what counts is what you can do.
On preview, also what Etrigan said. And Misantrophic Painforest.
posted by randomkeystrike at 1:16 PM on April 5, 2013
You should really only pursue a PhD if you're ~85-100% certain that it's what you want (and even then, your mind might change in the process). If you don't feel strongly about the subject, it will be hard to live on a small stipend and do work that might lead nowhere. A PhD shouldn't be a "bucket list" thing, especially in your early/mid 20s. It will take up a lot of your time--time with friends, time to build a career that isn't research-related, time to travel, time to be lazy. Is that what you want? You will be around 30 when you graduate--the rest of your 20s will be eaten up by the PhD. If that doesn't sound appealing.... ;)
For me, synthesizing research into logically tight papers is the ultimate payoff. There's something beautiful about it that is fulfilling in a way that nothing else is...and I have a lot of hobbies that are very dear to my heart. It's like the missing puzzle piece. If I didn't feel that way, I couldn't be doing graduate work. That being said, you don't need to be in academia--industry positions for people like you seem like they'd be plentiful. You have already been working with professors and PIs, and seem like you have a good idea of what research will be like. That's a positive thing.
Have you considered an interdisciplinary field? It doesn't need to be statistics or nothing. You might also consider a Masters degree.
posted by semaphore at 1:31 PM on April 5, 2013 [2 favorites]
For me, synthesizing research into logically tight papers is the ultimate payoff. There's something beautiful about it that is fulfilling in a way that nothing else is...and I have a lot of hobbies that are very dear to my heart. It's like the missing puzzle piece. If I didn't feel that way, I couldn't be doing graduate work. That being said, you don't need to be in academia--industry positions for people like you seem like they'd be plentiful. You have already been working with professors and PIs, and seem like you have a good idea of what research will be like. That's a positive thing.
Have you considered an interdisciplinary field? It doesn't need to be statistics or nothing. You might also consider a Masters degree.
posted by semaphore at 1:31 PM on April 5, 2013 [2 favorites]
I don't think you need a PhD...but have you considered an MS in biostats? I know too many people (okay, like 1 or 2) in my current workplace who do similar work to you, and who truly regret not having a Masters -- even though it's just a hoop to jump through, it would have helped their careers immensely.
With your skills, I would imagine you would be able to complete an MS in a relatively short amount of time. With an MS, I would think you could easily have academia/medical research job opportunities aplenty to "fall back on," should you decide to pick up and move far away, or get burnt out at Google or wherever. It's probably unfair, but I get a sense that many larger research institutions would automatically filter out applicants without a Masters.
posted by mean square error at 1:34 PM on April 5, 2013
With your skills, I would imagine you would be able to complete an MS in a relatively short amount of time. With an MS, I would think you could easily have academia/medical research job opportunities aplenty to "fall back on," should you decide to pick up and move far away, or get burnt out at Google or wherever. It's probably unfair, but I get a sense that many larger research institutions would automatically filter out applicants without a Masters.
posted by mean square error at 1:34 PM on April 5, 2013
p.s. you should do graduate school if, and only if, it's your passion, you want to be an academic for the rest of your life, and you can get funding.
Just as a counterpoint, this is not necessarily true in biology (except the funding part), in which a PhD can be a big help for advancing within industry. You can often graduate quite a bit faster than the Future Postdocs of America if you are clear about wanting a particular type of industry job up front and are proactive about applying during the last stages of your degree. I also have a friend whose BigPharma employer funded her PhD in exchange for signing a contract that she would stay on afterwards for a few years. So it's not a crazy question to ask, I think. The question is more whether this applies in OP's specific field.
OP, are you planning on staying in biology? If you're where I think you are, my impression is that there's a much bigger startup and startup-adjacent culture there vs. other academic bio programs - have you sync'ed up with those people at all?
As a side note...
What I am interested in, though, is writing code, playing with data, and the machine learning side of things. I feel more like I want to make things that other people can *use*, as opposed to producing insights that they can act on.
...I think this actually describes a few people in my PhD lab, at least to some extent - there was a big focus on making tools (complete with pretty web interfaces!) that are directly useful to and usable by wet-lab biologists, and we did a hell of a lot of machine learning and collaborate with some real heavyweights in that field (though personally, my own work was more in the "producing insights" paradigm and I'm not sure you'd be able to totally get away from that - it depends on what your department wants ultimately). I think it's worth at least looking at a few comp bio programs to see if there are people doing work that you'd click with.
If you want to do data science more broadly, an MS may or may not be useful - sort of out of my depth there.
posted by en forme de poire at 1:53 PM on April 5, 2013
Just as a counterpoint, this is not necessarily true in biology (except the funding part), in which a PhD can be a big help for advancing within industry. You can often graduate quite a bit faster than the Future Postdocs of America if you are clear about wanting a particular type of industry job up front and are proactive about applying during the last stages of your degree. I also have a friend whose BigPharma employer funded her PhD in exchange for signing a contract that she would stay on afterwards for a few years. So it's not a crazy question to ask, I think. The question is more whether this applies in OP's specific field.
OP, are you planning on staying in biology? If you're where I think you are, my impression is that there's a much bigger startup and startup-adjacent culture there vs. other academic bio programs - have you sync'ed up with those people at all?
As a side note...
What I am interested in, though, is writing code, playing with data, and the machine learning side of things. I feel more like I want to make things that other people can *use*, as opposed to producing insights that they can act on.
...I think this actually describes a few people in my PhD lab, at least to some extent - there was a big focus on making tools (complete with pretty web interfaces!) that are directly useful to and usable by wet-lab biologists, and we did a hell of a lot of machine learning and collaborate with some real heavyweights in that field (though personally, my own work was more in the "producing insights" paradigm and I'm not sure you'd be able to totally get away from that - it depends on what your department wants ultimately). I think it's worth at least looking at a few comp bio programs to see if there are people doing work that you'd click with.
If you want to do data science more broadly, an MS may or may not be useful - sort of out of my depth there.
posted by en forme de poire at 1:53 PM on April 5, 2013
Yeah, don't get a Ph.d. You'd hate it.
One thing you might want to do is check out the CDC for jobs in your area. Sure, Atlanta isn't San Francisco (not by a long shot) but you might find the challenge and the career path you're looking for.
Shit, the Government is ALWAYS hiring statisticians, and the pay is good, the benefits are great and you can work on some AMAZING projects.
Or, hang out in Silicon Valley, I'm sure there are ton of BioTech folks who want to slurp you up with a spoon.
Learn more, code more, become active in the coding communities.
Your future's so bright, you've gotta wear shades!
posted by Ruthless Bunny at 2:00 PM on April 5, 2013 [1 favorite]
One thing you might want to do is check out the CDC for jobs in your area. Sure, Atlanta isn't San Francisco (not by a long shot) but you might find the challenge and the career path you're looking for.
Shit, the Government is ALWAYS hiring statisticians, and the pay is good, the benefits are great and you can work on some AMAZING projects.
Or, hang out in Silicon Valley, I'm sure there are ton of BioTech folks who want to slurp you up with a spoon.
Learn more, code more, become active in the coding communities.
Your future's so bright, you've gotta wear shades!
posted by Ruthless Bunny at 2:00 PM on April 5, 2013 [1 favorite]
I write this as someone who has similar interests and who's wrestling with similar decisions.
I don't know what your undergrad was like and how you define "non-trivial" and "wet paper bag." You typically don't prove anything non-trivial in undergrad math, unless you take some graduate-level courses, and even then it's not a necessity.
In mathematical areas, an advanced degree really matters. "Five years and a BS" is not the same as "one year and a master's," there's a vast difference in competence. Many government quant positions will want to see an advanced degree, not an undergraduate degree plus experience.
My own experience with graduate-level coursework in applied math in particular is that you get to learn a lot more stuff. On one hand, it will build on the stuff you learned in upper-level undergrad courses, which are the foundation for everything that follows. I imagine undergrad gave you basic ideas about interpolation, optimization, approximation, quadrature, and so on. Each of these areas is rather enormous and has tons and tons of theory and algorithms to learn about, and even in graduate-level classes you barely scratch the surface.
Also, in my experience, math isn't very susceptible to self-study. I can't just sit down and read about applied linear algebra for fun the way I can read sociology or history. So, if you want to learn more cool stuff while living on a small fellowship, I guess there's that. Grad school, for all intents and purposes, is the only way to develop this expertise.
There's a lot of master's programs offering "terminal" master's degrees. And, in my ignorance and weakness, I have looked into a few of them. After meeting the students and faculty in these programs and completing one or more courses, I realized that I really, really dislike programs that don't bring up the student to something like the level of the instructor. The applied stats program I toyed with didn't train up students to be anything like actual statisticians, more like advanced button-pushers with some fuzzy intuitions about geometry and dimensionality. The "data science" master's program I looked at really felt like a joke. The students in it came from backgrounds that didn't include even rudimentary programming skills, so when it came time to build classifiers and extract features, they were completely, comically out of their depth. FWIW, the instructors in the program are all PhD-carrying computer scientists and computational linguists.
The only lesson I've learned so far is that, if anything, it makes sense for me to be a strong enough applicant to get into a rigorous PhD program and then think about bailing out with a master's, if it comes to that. At least it will be a degree I can consider intellectually honest. If you're feeling restless at work, why not set yourself the goal of being able to score well on the GRE math subject test? It'll be a productive use of your time and might reminds you about some of the realities of doing classroom math.
posted by Nomyte at 2:52 PM on April 5, 2013 [1 favorite]
I don't know what your undergrad was like and how you define "non-trivial" and "wet paper bag." You typically don't prove anything non-trivial in undergrad math, unless you take some graduate-level courses, and even then it's not a necessity.
In mathematical areas, an advanced degree really matters. "Five years and a BS" is not the same as "one year and a master's," there's a vast difference in competence. Many government quant positions will want to see an advanced degree, not an undergraduate degree plus experience.
My own experience with graduate-level coursework in applied math in particular is that you get to learn a lot more stuff. On one hand, it will build on the stuff you learned in upper-level undergrad courses, which are the foundation for everything that follows. I imagine undergrad gave you basic ideas about interpolation, optimization, approximation, quadrature, and so on. Each of these areas is rather enormous and has tons and tons of theory and algorithms to learn about, and even in graduate-level classes you barely scratch the surface.
Also, in my experience, math isn't very susceptible to self-study. I can't just sit down and read about applied linear algebra for fun the way I can read sociology or history. So, if you want to learn more cool stuff while living on a small fellowship, I guess there's that. Grad school, for all intents and purposes, is the only way to develop this expertise.
There's a lot of master's programs offering "terminal" master's degrees. And, in my ignorance and weakness, I have looked into a few of them. After meeting the students and faculty in these programs and completing one or more courses, I realized that I really, really dislike programs that don't bring up the student to something like the level of the instructor. The applied stats program I toyed with didn't train up students to be anything like actual statisticians, more like advanced button-pushers with some fuzzy intuitions about geometry and dimensionality. The "data science" master's program I looked at really felt like a joke. The students in it came from backgrounds that didn't include even rudimentary programming skills, so when it came time to build classifiers and extract features, they were completely, comically out of their depth. FWIW, the instructors in the program are all PhD-carrying computer scientists and computational linguists.
The only lesson I've learned so far is that, if anything, it makes sense for me to be a strong enough applicant to get into a rigorous PhD program and then think about bailing out with a master's, if it comes to that. At least it will be a degree I can consider intellectually honest. If you're feeling restless at work, why not set yourself the goal of being able to score well on the GRE math subject test? It'll be a productive use of your time and might reminds you about some of the realities of doing classroom math.
posted by Nomyte at 2:52 PM on April 5, 2013 [1 favorite]
Don't do a PhD, good god. You don't want an academic job, so you'll just be exactly where you are now, six years later, poorer and with less applied experience.
Speaking as a senior PhD student with software and stats experience who is moving into the 'data science' arena, let me suggest to you that you have an immensely valuable skill set right now (in fact, I bet you get MeFi mail trying to recruit you because of this question-- let us know if I'm right). And you're in the Bay Area. You want "1) lots of data, 2) interesting questions, 3) interesting systems/methods and 4) an engineering-first culture", where should you be looking? Walk around SoMa in San Francisco wearing a T-Shirt saying 'EXPERIENCED DATA SCIENTIST FOR HIRE' and people will throw job offers at your feet. I'm not really joking. Every big firm, like Google and Facebook and Twitter and LinkedIn, has a large data science and analytics team that needs exactly the skills you have. Startups like airbnb and a bajillion other ones live and die on the strength of their data/stats teams. You could command $100K without even sneezing. All you have to do is get yourself out there.
Insight is a good place to check out. Get on LinkedIn and target your profile towards the kind of work you want to do. You could also try some Meetup groups -- I hear recruiters often use these -- but the real benefit is to network with like-minded professionals, get added on LinkedIn, and make it known that you are looking for work, because lots of these people's companies will be actively recruiting.
posted by PercussivePaul at 2:59 PM on April 5, 2013 [1 favorite]
Speaking as a senior PhD student with software and stats experience who is moving into the 'data science' arena, let me suggest to you that you have an immensely valuable skill set right now (in fact, I bet you get MeFi mail trying to recruit you because of this question-- let us know if I'm right). And you're in the Bay Area. You want "1) lots of data, 2) interesting questions, 3) interesting systems/methods and 4) an engineering-first culture", where should you be looking? Walk around SoMa in San Francisco wearing a T-Shirt saying 'EXPERIENCED DATA SCIENTIST FOR HIRE' and people will throw job offers at your feet. I'm not really joking. Every big firm, like Google and Facebook and Twitter and LinkedIn, has a large data science and analytics team that needs exactly the skills you have. Startups like airbnb and a bajillion other ones live and die on the strength of their data/stats teams. You could command $100K without even sneezing. All you have to do is get yourself out there.
Insight is a good place to check out. Get on LinkedIn and target your profile towards the kind of work you want to do. You could also try some Meetup groups -- I hear recruiters often use these -- but the real benefit is to network with like-minded professionals, get added on LinkedIn, and make it known that you are looking for work, because lots of these people's companies will be actively recruiting.
posted by PercussivePaul at 2:59 PM on April 5, 2013 [1 favorite]
A link to Someone who went and did the Phd thing. Her story will move you in the appropriate direction.
I will also give you a short story about my eldest child who was not accepted to the Phd program in Applied Math at University after completing (with honors) the Master's Program. He is happily employed by a software firm doing their stats verification and testing. Happy as can be going to work every morning.
It's the work you do and the people you're with that makes it happen. The fantasy of the education sinecure is rapidly diminishing as MOOC's come into their own. To quote the above article "the full-time, tenure-track professorship is extinct."
posted by ptm at 6:19 PM on April 5, 2013
I will also give you a short story about my eldest child who was not accepted to the Phd program in Applied Math at University after completing (with honors) the Master's Program. He is happily employed by a software firm doing their stats verification and testing. Happy as can be going to work every morning.
It's the work you do and the people you're with that makes it happen. The fantasy of the education sinecure is rapidly diminishing as MOOC's come into their own. To quote the above article "the full-time, tenure-track professorship is extinct."
posted by ptm at 6:19 PM on April 5, 2013
You've heard lots of advice. I'll give you my take, which may be contrary to some of the previous advice. What will graduate school get you? In some fields it is absolutely necessary that you have an advanced degree unless you want to be a technician. I do not know if this is the case for your field. Advanced degrees however do tend to open doors to management/leadership/senior positions.
You are either the type of person who (1) would do well in graduate school, (2) do well in graduate school at select schools/programs, or (3) not do well/enjoy graduate school. There are some people who just love learning, have the motivation, and would succeed at Stanford or University of Nowhere. Some people could succeed if they were in the right graduate program. Every graduate program has different academic standards (i.e. amount of work required) and focus. And some people never want to sit in a classroom again. You need to figure out which type of person you are.
So my advice - if you are really thinking about this, try a masters degree. A masters degree is typically 2 years, so just about anyone can get through that. You may even be able to swing a part-time gig with your employer (who may pay for it) to take one class per semester. This may take a little longer, but you would get to keep some nice salary coming in. You'll figure out from a masters whether a PhD is really for you.
posted by aarondesk at 6:37 PM on April 5, 2013
You are either the type of person who (1) would do well in graduate school, (2) do well in graduate school at select schools/programs, or (3) not do well/enjoy graduate school. There are some people who just love learning, have the motivation, and would succeed at Stanford or University of Nowhere. Some people could succeed if they were in the right graduate program. Every graduate program has different academic standards (i.e. amount of work required) and focus. And some people never want to sit in a classroom again. You need to figure out which type of person you are.
So my advice - if you are really thinking about this, try a masters degree. A masters degree is typically 2 years, so just about anyone can get through that. You may even be able to swing a part-time gig with your employer (who may pay for it) to take one class per semester. This may take a little longer, but you would get to keep some nice salary coming in. You'll figure out from a masters whether a PhD is really for you.
posted by aarondesk at 6:37 PM on April 5, 2013
Let me add one more thing. Graduate school is not like undergraduate, or at least it shouldn't be. One of the challenges of undergraduate is that most students are only really prepared to do "real" independent mature work when they are seniors, but by this point most are just ready to get done and move on. Graduate school is really for people who are grounded in the fundamentals and are ready to really learn the nitty gritty details of that field.
posted by aarondesk at 6:47 PM on April 5, 2013 [1 favorite]
posted by aarondesk at 6:47 PM on April 5, 2013 [1 favorite]
You're already doing it, you don't need a PhD. Now if you desperately want one that's cool but you don't need one. If you like what you're doing just keep doing it and keep accepting interesting collaborations as they arise. If you publish once every two years you're going to have more papers, collaborators and research opportunities than the average PhD student does when they graduate anyway.
Having said that- I work with a lot of data scientists and it is a constant thing for them to keep up to speed and relevant. Some of the people I work with are 45, reflect for a while on the many, many, many platforms and languages they have worked in over their careers in data science and just think to yourself about sustaining a career for that long. It might be that in 10 years your skills aren't as relevant as they are now if you're not careful.
posted by fshgrl at 1:00 AM on April 6, 2013 [1 favorite]
Having said that- I work with a lot of data scientists and it is a constant thing for them to keep up to speed and relevant. Some of the people I work with are 45, reflect for a while on the many, many, many platforms and languages they have worked in over their careers in data science and just think to yourself about sustaining a career for that long. It might be that in 10 years your skills aren't as relevant as they are now if you're not careful.
posted by fshgrl at 1:00 AM on April 6, 2013 [1 favorite]
What I am interested in, though, is writing code, playing with data, and the machine learning side of things. I feel more like I want to make things that other people can *use*, as opposed to producing insights that they can act on. I think I would be at home in a more data science-ish role, or even as a software engineer.
if you like your job stay there for now. it sounds like it's giving good experience to continue to move forward in your career, as opposed to doing routine stuff that does not help you get ahead.
i think some people go to grad school for a masters in stats so that they can do a career change and get into just the kind of job you're in. if they don't have experience they need the degree as proof that they can do the work. since you're already in that kind of job it's not clear if going back to school could help you. on the one hand, maybe moving up is not possible because they require a degree. on the other hand, maybe it doesn't matter, and your work experience you have is proof enough that you know your stuff.
you should ask your boss, senior people at your job, senior people at meet-ups: will not having a MS or phd in stats limit me?
one middle ground may be to get a MS in stats by going to school part time.
as some background: different schools have different purposes for their degrees, both MS and PhD. some schools are professor factories, others are training to do statistic work in industries. an MS could be a stepping stone to a PhD, or it could be the not-going-to-be-a-professor track. there are also PhD programs that are for people who want to do stats work, but not be a professor. i've seen job listings that prefer a MS or PhD.
you can kind of figure it out by going to a schools website, and seeing where their recent grads are working. if that doesn't work, you could probably send a short email.
posted by cupcake1337 at 1:08 PM on April 6, 2013 [1 favorite]
if you like your job stay there for now. it sounds like it's giving good experience to continue to move forward in your career, as opposed to doing routine stuff that does not help you get ahead.
i think some people go to grad school for a masters in stats so that they can do a career change and get into just the kind of job you're in. if they don't have experience they need the degree as proof that they can do the work. since you're already in that kind of job it's not clear if going back to school could help you. on the one hand, maybe moving up is not possible because they require a degree. on the other hand, maybe it doesn't matter, and your work experience you have is proof enough that you know your stuff.
you should ask your boss, senior people at your job, senior people at meet-ups: will not having a MS or phd in stats limit me?
one middle ground may be to get a MS in stats by going to school part time.
as some background: different schools have different purposes for their degrees, both MS and PhD. some schools are professor factories, others are training to do statistic work in industries. an MS could be a stepping stone to a PhD, or it could be the not-going-to-be-a-professor track. there are also PhD programs that are for people who want to do stats work, but not be a professor. i've seen job listings that prefer a MS or PhD.
you can kind of figure it out by going to a schools website, and seeing where their recent grads are working. if that doesn't work, you could probably send a short email.
posted by cupcake1337 at 1:08 PM on April 6, 2013 [1 favorite]
This thread is closed to new comments.
p.s. you should do graduate school if, and only if, it's your passion, you want to be an academic for the rest of your life, and you can get funding.
posted by caek at 1:04 PM on April 5, 2013 [3 favorites]