Help me think of a tech job that isn't mind-numbingly boring?
October 16, 2020 11:54 AM Subscribe
I am a PhD student with a couple of years before I finish. I don't anticipate wanting to apply for postdocs/professorships, etc. after I graduate. I talk with some people who have gone into tech after finishing PhDs in my field, and the work they do sounds like it would really depress me. My research involves doing stuff with a bunch of buzzwords: 'scientific computing', 'machine learning' with 'deep neural network architectures', 'data visualization', statistical modeling, very much 'big data' kind of stuff. Is there a niche for me to work that will be gratifying?
My academic field is being notoriously and rapidly engineerified, much to its detriment, in my belief. Tech is absorbing a lot of researchers, but from my conversations with colleagues who have gone that route, they end up doing pretty boring, uncreative stuff, very much different from their previous research projects. Because, you know, capitalism and profit, etc. But unlike the few colleagues I have talked to, I have more a more attractive skillset from an industry perspective, the ones I mentioned above, because my research has always been more 'computational'.
I really want to do something that is, at the very least, creative with my time. I can deal with a pointless corporate profiteering setup as long as it's not depressingly boring, at least for the time it takes me to figure out what else I might want to do with the money-making portion of my life moving forward.
Do any of you who work in 'the industry' have specific ideas about whether there are particular niches I could fill that would meet that criteria? I don't really want to be a 'data scientist' or 'data engineer' or whatever the oxymoronic and/or redundant lingo is these days, but if there are jobs that fall under that rubric that I should look into, I'm happy to hear about them.
I didn't want to say upfront what my academic discipline is, but I can say that the data I work with most of the time is human speech (acoustics and phonetics). I just really don't imagine I would find it the least bit gratifying to write grammars for Alexa/Siri, etc. I feel dread about my graduation because I'm a sensitive person and it would destroy my soul to do stuff I found completely non-creative all day. Before starting the PhD I worked large corporate food service (you know, 'entry level'), and, yeah, I hated it. Yeah, I'd get paid a lot more to do stuff in tech, but to me that wouldn't come anywhere close to making up for the pain of drudgery.
Do you have any suggestions for specific things to look into or people to chat with?
My academic field is being notoriously and rapidly engineerified, much to its detriment, in my belief. Tech is absorbing a lot of researchers, but from my conversations with colleagues who have gone that route, they end up doing pretty boring, uncreative stuff, very much different from their previous research projects. Because, you know, capitalism and profit, etc. But unlike the few colleagues I have talked to, I have more a more attractive skillset from an industry perspective, the ones I mentioned above, because my research has always been more 'computational'.
I really want to do something that is, at the very least, creative with my time. I can deal with a pointless corporate profiteering setup as long as it's not depressingly boring, at least for the time it takes me to figure out what else I might want to do with the money-making portion of my life moving forward.
Do any of you who work in 'the industry' have specific ideas about whether there are particular niches I could fill that would meet that criteria? I don't really want to be a 'data scientist' or 'data engineer' or whatever the oxymoronic and/or redundant lingo is these days, but if there are jobs that fall under that rubric that I should look into, I'm happy to hear about them.
I didn't want to say upfront what my academic discipline is, but I can say that the data I work with most of the time is human speech (acoustics and phonetics). I just really don't imagine I would find it the least bit gratifying to write grammars for Alexa/Siri, etc. I feel dread about my graduation because I'm a sensitive person and it would destroy my soul to do stuff I found completely non-creative all day. Before starting the PhD I worked large corporate food service (you know, 'entry level'), and, yeah, I hated it. Yeah, I'd get paid a lot more to do stuff in tech, but to me that wouldn't come anywhere close to making up for the pain of drudgery.
Do you have any suggestions for specific things to look into or people to chat with?
I do database stuff for a university although i'm not an academic, I have a BS in CS, used to work at startups but that life got old, fast. I work here -- we help out lots of different science areas do research and support them with high performance computing and stuff. it's kind of bleeding edge and i like it, and I get to play around with lots of new technology. It's not anything like working at a real company though. I can talk to you more if you're interested, send me a memail.
posted by capnsue at 12:01 PM on October 16, 2020 [1 favorite]
posted by capnsue at 12:01 PM on October 16, 2020 [1 favorite]
What do you think of as “creative” vs. “non-creative”? That sounds like your biggest motivating factor.
I’m in “data science” (scare quotes because it’s a buzzword), and I find it satisfying and interesting to solve worthwhile problems using my computational skill set. I managed to get myself into computational toxicology (despite not actually having any sort of toxicology degree), so my “worthwhile problems” are about chemical safety.
Is it “creative” in your definition? I don’t know. I get to develop new tools and come up with new ideas about how to solve problems; it feels creative to me. But maybe you’d consider it “engineerified” (I’m not really sure what you mean by that in this context)?
I’ve worked in consulting and in government, and could also do what I do directly in private industry. It sounds like you’re assuming your only two options are “become a university professor” or “become a Big Tech developer”, but this is not the case. Scientific consulting is a thing (and it doesn’t need to be ultra-high-powered consulting with ultra-long hours). Government research is a thing. Heck, even being a non-professor university research scientist is a thing.
Comp-tox is far from the only field where someone with data science/machine-learning skills could get to do new science outside of academia. I would look outside of your specific subfield niche, and look up papers that take the kinds of algorithms you use and apply them to different problems. Do any of those sound like interesting problems?
posted by snowmentality at 12:16 PM on October 16, 2020 [6 favorites]
I’m in “data science” (scare quotes because it’s a buzzword), and I find it satisfying and interesting to solve worthwhile problems using my computational skill set. I managed to get myself into computational toxicology (despite not actually having any sort of toxicology degree), so my “worthwhile problems” are about chemical safety.
Is it “creative” in your definition? I don’t know. I get to develop new tools and come up with new ideas about how to solve problems; it feels creative to me. But maybe you’d consider it “engineerified” (I’m not really sure what you mean by that in this context)?
I’ve worked in consulting and in government, and could also do what I do directly in private industry. It sounds like you’re assuming your only two options are “become a university professor” or “become a Big Tech developer”, but this is not the case. Scientific consulting is a thing (and it doesn’t need to be ultra-high-powered consulting with ultra-long hours). Government research is a thing. Heck, even being a non-professor university research scientist is a thing.
Comp-tox is far from the only field where someone with data science/machine-learning skills could get to do new science outside of academia. I would look outside of your specific subfield niche, and look up papers that take the kinds of algorithms you use and apply them to different problems. Do any of those sound like interesting problems?
posted by snowmentality at 12:16 PM on October 16, 2020 [6 favorites]
Hi, I’m a former academic and I do data visualization and data engineering professionally now. Other than the red tape I have to deal with from managers and project leads I love it. It allows me to combine my analytical and creative/artistic brain to create stories with data that are also accurate and lead people to make insightful decisions. Plus it allows me to flex my graphic design and UI skills.
Like you I thought I would find the engineering aspect boring but if you create ETL pipelines in a program like SSIS (although people will argue against using it specifically) it is very similar to building a machine and can be quite fun (if extremely challenging sometimes). I don’t enjoy coding in SQL or Python all day but I DO get to utilize several languages in my toolbox when working in Power BI or Tableau to create visualizations so it never feels like I’m a data slave day in and day out.
I would avoid data science if you don’t want to be neck deep in complex code all the time TBH. I grew bored with machine learning very quickly, not because it is easy, but because it’s just not what jazzes up my brain.
So I would suggest looking into business intelligence and data visualization.
posted by Young Kullervo at 12:17 PM on October 16, 2020 [3 favorites]
Like you I thought I would find the engineering aspect boring but if you create ETL pipelines in a program like SSIS (although people will argue against using it specifically) it is very similar to building a machine and can be quite fun (if extremely challenging sometimes). I don’t enjoy coding in SQL or Python all day but I DO get to utilize several languages in my toolbox when working in Power BI or Tableau to create visualizations so it never feels like I’m a data slave day in and day out.
I would avoid data science if you don’t want to be neck deep in complex code all the time TBH. I grew bored with machine learning very quickly, not because it is easy, but because it’s just not what jazzes up my brain.
So I would suggest looking into business intelligence and data visualization.
posted by Young Kullervo at 12:17 PM on October 16, 2020 [3 favorites]
I'm a data analyst, currently at a startup that does water monitoring and is building smart cities infrastructure. It's fine. I like data analysis fine. I love my company and the work I do, because it's making the world a better place. When I leave this job, I'm looking at moving into more public-policy oriented companies, with a particular interest in analyzing housing resources (or lack thereof). I have to be creative and constantly learning, and while that's been hard during the pandemic when my brain isn't always working great, it does mean work is never dull. Startup culture is pretty bullshit and I don't know that I have another startup in me, but I was picky and got lucky, and if you're willing to take on the risk, it's definitely fast-paced and fascinating and lots and lots and lots of problem-solving. I'd start looking for companies who do something you can be passionate about, and who have a culture that vibes with you.
posted by kalimac at 12:17 PM on October 16, 2020 [2 favorites]
posted by kalimac at 12:17 PM on October 16, 2020 [2 favorites]
I'm a machine learning researcher in the private industry, We frequently hire new PhD students, preferring to hire those who have interned with us before. Have you done an industry research internship? Not only will it provide insight into What Do People Do All Day, but also give you vital contacts for later collaborations and job hunting. A successful internship all but guarantees a job interview after graduation, or even a straight offer if you impress your mentor.
My job -- and those of the people on my team -- is very similar to graduate school, except we're paid phenomenally well and there's no advisors. Like grad school, this kind of job is as creative as you make it. We have researchers who have been working on the same problem for five or six years, slowly refining their models and approach, and we have others who do all sorts of crazy stuff. As long as you publish regularly, you're largely left alone. Nobody I work with is bored.
So, short answer: I think you have an overly negative view of private research labs. Don't dismiss careers in the private industry so quickly.
posted by riotnrrd at 12:18 PM on October 16, 2020 [11 favorites]
My job -- and those of the people on my team -- is very similar to graduate school, except we're paid phenomenally well and there's no advisors. Like grad school, this kind of job is as creative as you make it. We have researchers who have been working on the same problem for five or six years, slowly refining their models and approach, and we have others who do all sorts of crazy stuff. As long as you publish regularly, you're largely left alone. Nobody I work with is bored.
So, short answer: I think you have an overly negative view of private research labs. Don't dismiss careers in the private industry so quickly.
posted by riotnrrd at 12:18 PM on October 16, 2020 [11 favorites]
Sorry to double-post so quickly, but I wish I could favourite Young Kullervo's post again. It absolutely describes what I do love about data analysis, the mix of art and science and the way you can be intensely creative and curious. (I am also extremely meh about ML, it's just not my thing. There's tons of other stuff to do in data science though!)
posted by kalimac at 12:19 PM on October 16, 2020 [2 favorites]
posted by kalimac at 12:19 PM on October 16, 2020 [2 favorites]
ML is currently "hot" in bioinformatics, mainly because the scale of research has grown to the point where a lot of training data now exists to try to elicit patterns that might be biologically relevant, as well as computational power that is effectively on-demand.
But a useful answer probably comes down to what you like, at the end of the day. Essentially, any field where there is a ton of data is a foundation upon which to do machine learning. If there are subjects you are more interested in than others, I'd see where those interests intersect with available data. There is a lot you could do in academia and industry.
posted by They sucked his brains out! at 12:20 PM on October 16, 2020
But a useful answer probably comes down to what you like, at the end of the day. Essentially, any field where there is a ton of data is a foundation upon which to do machine learning. If there are subjects you are more interested in than others, I'd see where those interests intersect with available data. There is a lot you could do in academia and industry.
posted by They sucked his brains out! at 12:20 PM on October 16, 2020
I too am having a hard time understanding what you mean with your stipulation that the work must be "creative." I'm a data scientist in the kind of roles it sounds like you don't want and I think my work is not creative in the sense I am not coming up with novel methodologies, no new algorithms or anything, but I am creative in the sense that I usually am building a whole analytical/software solution that is new for the company at least from scratch, and I have quite a bit of solution autonomy - in other words I control how I address the needs that are presented to me, I do literature review, I craft the thing specific to the needs, and that feels somewhat creative. If you need to be breaking ground on new methods all the time I would say look for roles that are "research scientist" rather than anything with "data"/computational something or other in the title. But sounds like maybe you don't want to even be a research scientist for something like voice assistants, so can you be more specific about what the day-to-day tasks you do enjoy are? Probably full control over your time and research direction is scarce outside academia but you can find people in industry at the top places coming up with genuinely novel stuff, but is that what you want? I can't really tell
posted by slow graffiti at 12:33 PM on October 16, 2020 [3 favorites]
posted by slow graffiti at 12:33 PM on October 16, 2020 [3 favorites]
"... data I work with most of the time is human speech (acoustics and phonetics). I just really don't imagine I would find it the least bit gratifying to write grammars for Alexa/Siri, etc."
If your background is in speech recognition, language understanding or related fields, you can pretty much choose any of the big tech companies (Google, Amazon, Microsoft, Nuance, Facebook, etc.) to work for and seek out projects at the closest to core research per your preferences. I work in the field in a non-technical role and any of these companies and many others have big research groups. Some are "purer" than others, but the transition doesn't necessarily need to be that big (except for compensation).
posted by zeikka at 1:06 PM on October 16, 2020 [3 favorites]
If your background is in speech recognition, language understanding or related fields, you can pretty much choose any of the big tech companies (Google, Amazon, Microsoft, Nuance, Facebook, etc.) to work for and seek out projects at the closest to core research per your preferences. I work in the field in a non-technical role and any of these companies and many others have big research groups. Some are "purer" than others, but the transition doesn't necessarily need to be that big (except for compensation).
posted by zeikka at 1:06 PM on October 16, 2020 [3 favorites]
I'm a social scientist-turned-"data scientist" and I ended up at a government non-profit. I don't get paid a bazillion dollars like other folks, but the work I do is very satisfying. I've literally seen some of the stuff I've worked on influence policy for the better. There's a fair amount of creativity in data for government right now because, well, government stuff tends to be a bit behind the times (and subject to a lot of bureaucracy/ethical considerations) -- you've gotta be creative in how to work with what you've got/pitch implementation of things you need. Another thing is that it's allowed me to flex the teaching skills I gained in grad school because a lot of government folks are *really* not techy, so explaining ML/data pipelines/analysis/etc. requires a fair amount of consideration. A lot of people find the minutiae of policy pretty boring but I've come to find it super interesting AND I don't have to feel too scummy about the work I do.
posted by thebots at 1:22 PM on October 16, 2020 [4 favorites]
posted by thebots at 1:22 PM on October 16, 2020 [4 favorites]
First of all, congrats on generally being in the right place at the right time. Not for the usual reasons (max out $$$ at a FAANG company!) but for the sense that the rising tide (of wages) lifts all ships (of other wages) for what you want to do, so you can trade off some $$$ for some joy, which is, in my opinion how the game should be played.
Work for a small startup (less than 50 people, less than series B funding), then you are practically guaranteed not to be bored: you'll either be hooked or burnt out within a year. You appear to have "general data familiarity" so if you aren't wedded to speech analysis, read through Bret Victor's schtick about climate change and consider one of those jobs, like at Upstream Tech, Development Seed, Climate AI. There are plenty of others.
If research excites you, add "Research" to the end of a current monopoly, like Google Research or Microsoft Research. These organizations have fairly limited relationships with the mothership and mostly the researchers are there to publish. And they do cutting-edge stuff, especially at Microsoft.
But it sounds like you generally want to stay far away from putting ads on webpages or implementing "Like" buttons. Maybe think about a place like Whisper, which is doing 'AI for hearing aids'?
posted by tmcw at 1:26 PM on October 16, 2020 [1 favorite]
Work for a small startup (less than 50 people, less than series B funding), then you are practically guaranteed not to be bored: you'll either be hooked or burnt out within a year. You appear to have "general data familiarity" so if you aren't wedded to speech analysis, read through Bret Victor's schtick about climate change and consider one of those jobs, like at Upstream Tech, Development Seed, Climate AI. There are plenty of others.
If research excites you, add "Research" to the end of a current monopoly, like Google Research or Microsoft Research. These organizations have fairly limited relationships with the mothership and mostly the researchers are there to publish. And they do cutting-edge stuff, especially at Microsoft.
But it sounds like you generally want to stay far away from putting ads on webpages or implementing "Like" buttons. Maybe think about a place like Whisper, which is doing 'AI for hearing aids'?
posted by tmcw at 1:26 PM on October 16, 2020 [1 favorite]
Is there something outside of your work that you’re passionate about? The skills you have could be used in so many ways, not just in tech. For example I have a friend with a PhD in neuroscience who got a job in sports analytics.
posted by cali at 1:49 PM on October 16, 2020
posted by cali at 1:49 PM on October 16, 2020
I work on the eng side of a team that includes speech researchers at a FAANG. The research people seem pretty fulfilled to me -- it's definitely real research, not just writing grammars. Caveat is that most/all of them have CS-related PhDs, so if yours is in something considered "softer" like linguistics, it will be tough to break in. For example, you'll be expected to write C++ code, not just Python, that is at least vaguely production-ready. I know some other co-workers have (non-computational) ling PhDs and they are now working as program managers, which is a totally different job with zero research, albeit for a speech-related product.
posted by serelliya at 3:57 PM on October 16, 2020 [1 favorite]
posted by serelliya at 3:57 PM on October 16, 2020 [1 favorite]
I think I'm the third or fourth person to chime in with the same question - why aren't you considering private research labs? I also work at a large tech company that has a large research group that focuses on audio processing problems. They function more like an academic group than anything else - they regularly publish their research and continue to be part of their research communities. They aren't pressured to come up with solutions for immediate business problems. They also have access to large audio datasets that aren't available publicly and don't have to deal with finding funding for grants. As far as I can tell, they spend most of their time thinking about their work and deal with much less process than the average person at the company. Also, note, I am a software engineer who supports said researchers - my company has enough funding to pay engineers to build the "boring" parts like writing grammars and adapting your research to something that can actually be delivered to users. I think the technical (i.e. whether or not you can write C++ vs Python) requirements for each lab vary, as well - don't let that scare you away from looking through these jobs if they could fit what you're looking for.
Feel free to DM me if you want more details.
posted by rhythm and booze at 4:21 PM on October 16, 2020 [2 favorites]
Feel free to DM me if you want more details.
posted by rhythm and booze at 4:21 PM on October 16, 2020 [2 favorites]
I’ve been working in tech since 1999, so I’m at a different stage in my career. Looking back, my advice would be to reconsider the virtues of a job you can do well/exceed expectations in... but don’t feel passionate about.
A lot of employers will try to sell you on the need to be passionate about whatever their vision is. The hidden angle here is that getting you to overcommit to their vision serves their profit motive way more than it does yours.
A somewhat mundane job you can excel in allows you to keep your passions/excitement/energy for your own projects, whatever they may be. It’s a different kind of career, but it is an option.
One of the smartest engineers I have worked with negotiated a three-day work week so they could use the other four days for their own interests. Another established a career where they repeatedly worked “real jobs” full-time for 2-3 years, saving up enough money in the process to take a similar amount of time off for passion projects.
If you have any intent to commercialize your passion projects you need to pay close attention to the IP agreements you’re asked to sign, but finding employers with terms that are fair to you is possible.
posted by FallibleHuman at 4:23 PM on October 16, 2020 [6 favorites]
A lot of employers will try to sell you on the need to be passionate about whatever their vision is. The hidden angle here is that getting you to overcommit to their vision serves their profit motive way more than it does yours.
A somewhat mundane job you can excel in allows you to keep your passions/excitement/energy for your own projects, whatever they may be. It’s a different kind of career, but it is an option.
One of the smartest engineers I have worked with negotiated a three-day work week so they could use the other four days for their own interests. Another established a career where they repeatedly worked “real jobs” full-time for 2-3 years, saving up enough money in the process to take a similar amount of time off for passion projects.
If you have any intent to commercialize your passion projects you need to pay close attention to the IP agreements you’re asked to sign, but finding employers with terms that are fair to you is possible.
posted by FallibleHuman at 4:23 PM on October 16, 2020 [6 favorites]
DM me. Similar background as you and my job is a lot of fun, though of course, YMMV. And I didn’t have to make a field change.
posted by redlines at 4:41 PM on October 16, 2020
posted by redlines at 4:41 PM on October 16, 2020
Here’s another take, sometimes difficult to see from within the academic pipeline: there are many, many, many great jobs for people with strong scientific and technical backgrounds that do not involve doing whatever you mastered in grad school.
I have a PhD in the natural sciences and, through a weird series of events, ended up in scientific IT at a major pharmaceutical company. I have not worked in a lab in decades, and though I have done computational work in the past, at this point I couldn’t program my way out of a wet paper bag. I do have enough mastery and understanding of both science and tech to be a bridge between them in a job that’s creative and fun, at a company I love that does amazing things, for great money. About a third to a half of the people in my IT division have advanced degrees (Masters or PhD) in a scientific field. In my huge company, people end up in all kinds of organizational roles from a scientific starting point, and it matters a lot, because we are fundamentally a science and health business and every single function requires understanding of the business.
All this to say: whatever career paths your PI/department/conferences have show you is only a slice of what is really out there. If you’re hired in with a PhD in industry, in whatever role, they’re going to put you in a role where you have freedom to take the initiative and be creative.
Sounds like you’re kinda burnt out. Grad school will do that to you. Get your degree, get out of the hothouse of academia, try some stuff, it’ll sort itself out. Good luck.
posted by Sublimity at 4:45 PM on October 16, 2020 [3 favorites]
I have a PhD in the natural sciences and, through a weird series of events, ended up in scientific IT at a major pharmaceutical company. I have not worked in a lab in decades, and though I have done computational work in the past, at this point I couldn’t program my way out of a wet paper bag. I do have enough mastery and understanding of both science and tech to be a bridge between them in a job that’s creative and fun, at a company I love that does amazing things, for great money. About a third to a half of the people in my IT division have advanced degrees (Masters or PhD) in a scientific field. In my huge company, people end up in all kinds of organizational roles from a scientific starting point, and it matters a lot, because we are fundamentally a science and health business and every single function requires understanding of the business.
All this to say: whatever career paths your PI/department/conferences have show you is only a slice of what is really out there. If you’re hired in with a PhD in industry, in whatever role, they’re going to put you in a role where you have freedom to take the initiative and be creative.
Sounds like you’re kinda burnt out. Grad school will do that to you. Get your degree, get out of the hothouse of academia, try some stuff, it’ll sort itself out. Good luck.
posted by Sublimity at 4:45 PM on October 16, 2020 [3 favorites]
Before starting the PhD I worked large corporate food service (you know, 'entry level'), and, yeah, I hated it
There’s lots of good advice above about finding the perfect niche, but I just want to point out that even average software jobs are going to be very different from corporate food service.
I work as a software developer in a staid, widely-considered-boring field and I did many “entry-level” service jobs before that. The software work has been immensely more interesting and creative than the previous jobs. I solve problems all day, working with a team of smart people! It’s inherently a creative and collaborative activity, even if the end product doesn’t thrill you, and even if you think the problems aren’t important.
posted by ripley_ at 9:56 PM on October 16, 2020
There’s lots of good advice above about finding the perfect niche, but I just want to point out that even average software jobs are going to be very different from corporate food service.
I work as a software developer in a staid, widely-considered-boring field and I did many “entry-level” service jobs before that. The software work has been immensely more interesting and creative than the previous jobs. I solve problems all day, working with a team of smart people! It’s inherently a creative and collaborative activity, even if the end product doesn’t thrill you, and even if you think the problems aren’t important.
posted by ripley_ at 9:56 PM on October 16, 2020
Groups monitoring hate speech online have trouble keeping up with deliberate misspellings of slurs (they aim to fly under the radar). Identifying bots spewing misinformation and hate on e.g. Twitter is a problem as well (this has to be done manually). The Canadian Government just announced a ton of funding for tech groups to combat misinformation and hate speech (so I’m sure there are opportunities on the way). I can’t imagine it’s emotionally easy work, but it is absolutely necessary, and I doubt it’s boring.
posted by cotton dress sock at 12:36 PM on October 17, 2020 [3 favorites]
posted by cotton dress sock at 12:36 PM on October 17, 2020 [3 favorites]
This thread is closed to new comments.
posted by chesty_a_arthur at 11:59 AM on October 16, 2020 [1 favorite]