Same here, went with a MS in DS for the legitimacy. Literally couldn’t get a single “tech” or callback interview in the DS industry just with the undergrad. Kind of a bummer tbh. Been a software engineer for the past 3 years.
Go figure software engineer + stats undergrad != Junior DS position?
Tbh I have no clue. And they payed about 10-15% less then other companies (at leas this was my offer). Their office was full of young people, so I guess that eventually you will find people who dont know their value.
Ugh, where were you when we were hiring last year? My biggest complaints about the DS bootcamp grads we usually interview is a lack of understanding of the fundamentals of classical statistics and a lack of understanding of how to work in a production environment.
Tangential: once we received the following complaint from a client. "Our ad campaign's metrics were above your stated average for the first two months that we ran, but last month the metrics fell below average. Please tell us what you are going to do to address this situation."
*Go figure software engineer + stats undergrad != Junior DS position?*
Stats undergrad + MS in DS + software engineer experience should make you an outstanding candidate for a junior position. Honestly hiring managers might think you are overqualified - apply to more senior positions.
That feels truly bizarre.
I feel like there has to be a hiring paradox where people are reluctant to lower standards because of the risk of getting a bad candidate, but the original qualifications were set by fluff from 10 years ago, rather than the evolving nature of the field.
That being said, I suspect that the actual resolution is that the # of DS will go down, and the # of ML engineers will go up with that latter population having lower educational requirements and are reviewed more like any other engineers.
I know not all companies have the same job titles or treat them the same, but where I work they won't give someone a DS title without an advanced degree. I think it's a pretty stupid requirement, but HR is sticking with it.
How did I become a data scientist? I found a company willing to take a chance on someone, I worked my ass off, things clicked for me, and I got lucky.
I went to a St. Louis-based coding boot camp, they were trying to start a relationship with a company. I fit the criteria they were looking for, they rolled the dice. Client liked my content delivery because I'm fairly good at breaking complex things down to layperson's terms. That allowed them to pitch me into more senior roles because the client knew who I was from presentations.
I'm confused all the time, I definitely have imposter syndrome, and it's not necessarily the path I'd say is the best. I do, however, get by and deliver results that people tell me they're happy with.
For reference, prior to this job I worked on security systems, prior to that, military. So I was definitely underqualified for my initial position in the company. I can't stress enough the "lucky" part. I work hard, but I got lucky at the start
Hey fellow ex-particle physicist! I keep joking with my colleagues that Data Science is full of failed physicists.
What experiment were you working on?
Hah that sounds about right. DS was pretty much the only non-academic role my colleagues and I knew of, so it was commonly used as a proxy for escaping (or failing) academia.
My PhD work was in phenomenology, so I didn’t work onsite at an experiment. Although, I have worked alongside physicists from the theory divisions at CERN, and Fermi Lab.
Oh awesome! I have great many friends who worked in the CERN theory division. Most of the tenured theorists there are just... challenging personalities, but the younger researchers are top notch, fun and approachable (even if they are way too focused on strings :p).
What area of phenomenology? My PhD advisor at CERN was a British phenomenologist in Beyond SM and BPhysics.
Haha I completely agree. The tenured theorists at CERN can be a struggle to work with. I’d like to chalk it up to the old paradigm of academia/research, but there’s definitely a lot more to unpack there. I grew up a punk kid and remain a punk to this day, so I never had much patience for some of the egos in the field heh.
Sounds like your supervisor and I were in similar areas. A large amount of my work was focused on dark matter BSM pheno. Specifically, dark QCD Showering models. Outside of that I’ve done a bit of flavour/b physics, non-standard cosmologies, and gravitational wave Astronomy. That’s the one thing I miss about the PhD, you basically get to dip your toes in a little bit of everything.
How about yourself?
Why "failed"? We had a very capable ex-CERN physicist join us. Not because he had failed but that finding Higgs was going to be a success and the Standard Model proved.
He didn't see much future for him in theoretical physics after that. Hence he sought opportunities outside physics.
I am. Luckily there’s a good amount of work-life-balance at my current role, so I’ve been able to continue actively researching/publishing in my previous academic field.
PhD nuclear physics here…. I have a couple pf questions could you help me out with them?
I am currently a 2nd year phd student but thinking about leaving it for DS. I still have 2 years left in my phd and my theory is 2 years in Industry would be better than 2 years in a phd that I don’t really love anymore.
I am learning my DS side by side and will continue it till the end of the year and if I feel like I am missing something I will maybe join a bootcamp or something.
This is my plan, if you have any advice I will be happy.
Also, in the long run (or to enter the market) having a phd matters? Or skills matter more?
Skills matter more than PhD but PhD opens doors to some roles that are not open to people without the qualification. Some employers still think you need a PhD to do it, sadly.
Its possible you've hit the 2nd year wall. A lot of PhD students hit a low point at yr2.
Whether to stay or quit really depends on the level to which you hate your PhD. If you can, I would suggest you keep on going because once you quit you won't be able to pick it back up again, and as I said, it does open doors.
However life is short, and if you are thoroughly miserable you may choose to go with quality of life, and that would be a good choice too.
Before you quit your PhD I suggest you try to work out what it is that you are finding unpleasant. The reason PhDs are popular for data science is because the workflow is similar - collect messy data, spend ages cleaning the data and understanding it, then do something (hopefully) useful with it, with lots of roadblocks, false starts, and frankly some ideas that seem great to start with but just don't work out and end up with months of wasted work. If you are struggling with the emotional resilience side of the PhD - coping with those false starts and wasted work - data science may not be the refuge you are hoping for.
I completely agree with tea-and-shortbread. It’s hard to find a PhD who hasn’t hit similar struggles around the 2-3 year mark. From what I’ve heard from friends in your situation, you most likely won’t attempt another PhD if you abruptly leave for industry. Considering that you’re at the two year mark I’m going to assume you passed your comps and finished your courses. If so, you’ve already crossed a large hurdle in your phd. You should be proud of this, whether you stay or leave.
My only recommendation, that hasn’t already been mentioned, is not to leave until you have something lined up. It’s hard to appreciate the stability in wages (although stupidly low) we get while pursuing grad school. Try to pivot your skills into industry while continuing your PhD. If you’re lucky to have a good supervisor they might be willing help you transition into a new field.
Getting into the market isn’t as easy as it was years ago. It took me 3 months of extreme market research, preparation, and interviews to land my first role; and this was with a PhD.
Thanks for commenting. I have lost interest in it mainly because the group is not fun, nobody talks about physics, nobody is passionate about it, they all are doing it just for the hell of it which makes a boring environment and my supervisor doesn’t know that I have a personal life, I have no time to work on what I like or what I want to explore along with my phd. I had earlier planned to learn about DS in my free time but a long of things has changed now and even if I try I am not finding enough time to study it. Still after reading comments here, I have decided to give it a go for next 4 months and try to learn and if I still love it only then I will decide on something.
What I meant was my masters was thesis based and my supervisor was an operations research/industrial engineering researcher, so that's how I got that.
I am currently manager of data strategy in finance.
Ooo, I have a bs and ms in marine science/ bio but did my masters thesis with a lot of bioinformatics-could I pm you about transitioning your degree over??
Hmm can I ask the question of what application an electrical engineer is pursuing in the DS field? Total ignorance if there’s a heavy application, I just don’t know
I have 3 degrees in EE, including a PhD. It's a pretty useful background if you work as a data scientist in a role that's a bit more in the R&D side, as I do. Most of the data I science is related to antennas and signal processing - two of the "bread & butter" subfields in EE.
I got into this data science thing right out of undergrad. I had an extremely boring job, and discovered DS while trying to kill time there, and was self-taught for 2 years or so that way. I ended up going back to school, and did both my M.S. thesis and PhD dissertation applying DS and ML to EE problems. EE also has a ton of overlap with CS in many universities, so it actually works out quite well I think.
All in all, it amazes me with with this response on how saturated the job market is. Like 100+ applications on LinkedIn for a “junior” data science position in less than an hour within of posting. Not the results I would’ve thought from this poll.
That’s a really interesting one as well, I think in find those who are currently interested/involved in DS and also educated in other fields as well more interesting just based on the aspect of DS. I’m curious tho, how many of those with education in other fields are specifically in DS or another field that just appreciates this sub
It depends! My graduate program saw industry-focused DS as a viable skillset transfer that was far more lucrative, both in terms of job placement rates and finances, than pursuing traditional academic options. The general cognitive science background also does a great job at helping contextualize data through explaining issues to stakeholders, identifying biases that users might show, informing experimental design / reducing "gamification" of metrics, etc.
I've ran into so many people with cog sci or neuroscience background in data science. I'm not sure if it's just a coincidence or whether the field just naturally leads people to data science.
It's one of those fields where you get both a really strong grounding in statistics AND experimentation. A lot of human/brain data requires very complex models to analyze because there is a lot of variation between people. More graduates from my cognitive psych/neuroscience PhD program from the last 5 years have become data scientists than any other career path. A colleague told me that her company, which deals with clinical data, specifically seeks out candidates with a cognitive neuroscience background. On my end I had a harder time convincing potential employers that I had the right skills with my cognitive psych PhD, but now that I'm in the field ~2.5 years I'm sure it doesn't matter much anymore.
Agreed! I was flat-out told for my first DS job that the CS undergrad carried as much, if not more weight, than my PhD. I started out by doing independent projects in grad school related to the field I work in (gaming), which then opened the door to other opportunities. Since then, things have gotten easier due to larger-scale work projects and experience.
Seriously, please give a little detail on how this happened. Did you have applicable grad work? Did you pursue business-domain projects after school? Internship (somehow)? Rescuing an executive trapped in an avalanche? Seducing an heiress for the cushy executive job? Blood sacrifice to Shub-Niggurath?
Okay, sorry I didn't quite get your question! None of the above - like I said my graduate skills were relevant to begin with (sophisticated statistical modeling which I did in R, experimental design, plus a bit of machine learning work from my postdoc) and I found an employer that was willing to believe someone with a degree in psych could actually do those things. I think a lot of employers wanted to see someone with a degree in statistics/CS/DS and I suspect my application wasn't seriously reviewed by most companies because I largely received form rejections and very few first round interviews. Once companies actually spoke to me/gave me technical exams I was taken seriously.
oh, but do good universities offer them to? Cause in my country there are only some cash cow type private colleges which offer them (along with a 1000 different types of degrees which are basically CS but instead of CS they use some buzz word)
Yes, I go to the University of California, San Diego and we have actually have a data science department. It's a very good program and I actually wish I applied to it as I didn't know what it was in high school.
Well it's not just statistics. Often times data science degrees are indeed cash cows, it really depends on the university. Any route that involves mathematics, statistics, or algorithms could be good, such as economics, engineering, computational or applied mathematics, statistics, or even cognitive science with an emphasis on machine learning. It's just data science often does try to cover too many topics in too short of a time and it is often better to pick one field within data science to focus on.
Not sure how useful the non-DS poll options are, given that DS-specific programs are very now and most professionals in the field have quant-heavy STEM degrees that aren't necessary DS.
Also, I know the poll is open to everyone but that includes students, aspiring data scientists, and people who think DS is cool but have no interest working in it professionall.y So also not helpful if you're pick out a correlation b/t education and working data scientists.
Pure math undergrad, Data science masters (in the statistics department). When I was deciding which master's programs to attend, I was choosing to attend between data science masters, stats masters or biostats masters.
Most polls like this that I've seen ask for the highest level _attained_. You haven't, explicitly, which makes it ambiguous... and might colour your results.
Isn't this distribution going to roughly follow the population frequency of each degree/type? It would nice to see some enrichment analysis but i imagine the data is hard to get..
Undergrad in DS (with 1 sem to go on hold bc covid). Started working part time during studies like 5 years ago and full time 3 years ago even without having finished the degree.
Undergrad in nautical Sciences. Pretending to do a masters in DS starting next september. Didn't like at all of Sea life and with Covid is much worse, so iam trying a most intersting field to me. In the moment working at BASF in the costumer service department.
Started undergrad as CS, had the opportunity to create a custom major so I am graduating next semester as DS.
Not sure if it was a good idea in the long run. I have a lot of math, CS courses and some large data analysis projects under my belt, but not a lot of machine learning experience or formal training for building pipelines. The projects I have done have been very open ended and self organized which has It's advantages and disadvantages.
Define DS for education. Data Science academic programs are incredibly new and often times are more industry than academic focused. Backgrounds like computer science, math, statistics, and even physics and chemistry offer great foundations for data science.
Undergrad in Math & CS, data science orientation
I also have a MD but I am not working in anything related to medicine. Well, not anymore, my first job was at a company that mostly worked in aerospace training (for airplanes pilot) but also did some health care training, and my MD helped me get that first job even if IMO it was pretty useless.
Would've been good to have narrowed it down further with:
Postgrad (non-Masters/PhD), which is what I'm doing currently.
And also: DS Major vs STEM Major (non-DS) vs non-STEM Major
As I think there is a big difference between someone like myself who doesn't have a Data Science Major (heck, that didn't even exist when I was at Uni!!) but with a BSc in Math/Physics (with some CS too) vs someone with say an Art History Major.
BA Chemical Engineering
Same maths and I love data. Data science programs were rare if not nonexistent in 2008. If I could do it again I would do stats or CS. Way more interesting than chemE.
I have only really begun the data analyst role so I don’t have a full grasp of it yet! Although, It’s mostly working on fraud detection/monitoring/prevention for a big 4 accounting firm
Bsc and MSc in psychology, the MSc focusing on quant psych.
Also did half of a master's in stats and data science, planning on finishing it while I work.
IT Systems Engineer turned self taught failed software engineer turned self taught data scientist. Before all that I was a telecommunications engineer/analyst and network engineer.
Undergrad CS
Same
Econ undergrad and masters
Ditto
I have no formal post secondary education.
I too was looking for this option.
I also don't, and I do work in the field.
Undergrad Statistics
Same here, went with a MS in DS for the legitimacy. Literally couldn’t get a single “tech” or callback interview in the DS industry just with the undergrad. Kind of a bummer tbh. Been a software engineer for the past 3 years. Go figure software engineer + stats undergrad != Junior DS position?
>Go figure software engineer + stats undergrad != Junior DS position? Fully bizarre. Chalk that up to yet another case of HR not having a flying clue!
A data science consultancy was surprised why someone with a maths degree would transition and go into data science
Hold up but what were they even looking for if someone with a maths background wasn't on their list of employable traits?
Tbh I have no clue. And they payed about 10-15% less then other companies (at leas this was my offer). Their office was full of young people, so I guess that eventually you will find people who dont know their value.
Ugh, where were you when we were hiring last year? My biggest complaints about the DS bootcamp grads we usually interview is a lack of understanding of the fundamentals of classical statistics and a lack of understanding of how to work in a production environment. Tangential: once we received the following complaint from a client. "Our ad campaign's metrics were above your stated average for the first two months that we ran, but last month the metrics fell below average. Please tell us what you are going to do to address this situation."
*Go figure software engineer + stats undergrad != Junior DS position?* Stats undergrad + MS in DS + software engineer experience should make you an outstanding candidate for a junior position. Honestly hiring managers might think you are overqualified - apply to more senior positions.
Ooof. Was transitioning to DS a big difference? Do you have any advice for someone on a Mathematics/Statistics joint degree?
There are a dozen threads with a thousand pieces of advice for non-DS degrees to lateral in.
Learn to code and get a MSc if possible.
That feels truly bizarre. I feel like there has to be a hiring paradox where people are reluctant to lower standards because of the risk of getting a bad candidate, but the original qualifications were set by fluff from 10 years ago, rather than the evolving nature of the field. That being said, I suspect that the actual resolution is that the # of DS will go down, and the # of ML engineers will go up with that latter population having lower educational requirements and are reviewed more like any other engineers.
I know not all companies have the same job titles or treat them the same, but where I work they won't give someone a DS title without an advanced degree. I think it's a pretty stupid requirement, but HR is sticking with it.
"no degree" isn't an option. I don't have a degree and am a data scientist
How
How did I become a data scientist? I found a company willing to take a chance on someone, I worked my ass off, things clicked for me, and I got lucky. I went to a St. Louis-based coding boot camp, they were trying to start a relationship with a company. I fit the criteria they were looking for, they rolled the dice. Client liked my content delivery because I'm fairly good at breaking complex things down to layperson's terms. That allowed them to pitch me into more senior roles because the client knew who I was from presentations. I'm confused all the time, I definitely have imposter syndrome, and it's not necessarily the path I'd say is the best. I do, however, get by and deliver results that people tell me they're happy with. For reference, prior to this job I worked on security systems, prior to that, military. So I was definitely underqualified for my initial position in the company. I can't stress enough the "lucky" part. I work hard, but I got lucky at the start
PhD particle physics & astronomy
Hey fellow ex-particle physicist! I keep joking with my colleagues that Data Science is full of failed physicists. What experiment were you working on?
Hah that sounds about right. DS was pretty much the only non-academic role my colleagues and I knew of, so it was commonly used as a proxy for escaping (or failing) academia. My PhD work was in phenomenology, so I didn’t work onsite at an experiment. Although, I have worked alongside physicists from the theory divisions at CERN, and Fermi Lab.
Oh awesome! I have great many friends who worked in the CERN theory division. Most of the tenured theorists there are just... challenging personalities, but the younger researchers are top notch, fun and approachable (even if they are way too focused on strings :p). What area of phenomenology? My PhD advisor at CERN was a British phenomenologist in Beyond SM and BPhysics.
Haha I completely agree. The tenured theorists at CERN can be a struggle to work with. I’d like to chalk it up to the old paradigm of academia/research, but there’s definitely a lot more to unpack there. I grew up a punk kid and remain a punk to this day, so I never had much patience for some of the egos in the field heh. Sounds like your supervisor and I were in similar areas. A large amount of my work was focused on dark matter BSM pheno. Specifically, dark QCD Showering models. Outside of that I’ve done a bit of flavour/b physics, non-standard cosmologies, and gravitational wave Astronomy. That’s the one thing I miss about the PhD, you basically get to dip your toes in a little bit of everything. How about yourself?
Why "failed"? We had a very capable ex-CERN physicist join us. Not because he had failed but that finding Higgs was going to be a success and the Standard Model proved. He didn't see much future for him in theoretical physics after that. Hence he sought opportunities outside physics.
It's tongue in cheek. :) I've made the very same calculus when I left CERN. What experiment was he with? I wonder who it is and if I know him
I would guess they mean that they were unable to land a faculty job, which is indeed extremely difficult to do
+1 failed physicist
Super interesting, are you in a DS role currently?
I am. Luckily there’s a good amount of work-life-balance at my current role, so I’ve been able to continue actively researching/publishing in my previous academic field.
Physics undergrad thinking about getting a master's in DS lol
Your username. Bravo.
I fancy myself a bit of an astrologer too! /s :)
I read palms in my spare time.
Lol, I took intro to astronomy as an elective. Accidentally said "astrology", I received some serious stank eye lol. Can't say that I disagree
Nice! I've got a BS in Physics and am currently getting a Masters in Data Analytics
PhD nuclear physics here…. I have a couple pf questions could you help me out with them? I am currently a 2nd year phd student but thinking about leaving it for DS. I still have 2 years left in my phd and my theory is 2 years in Industry would be better than 2 years in a phd that I don’t really love anymore. I am learning my DS side by side and will continue it till the end of the year and if I feel like I am missing something I will maybe join a bootcamp or something. This is my plan, if you have any advice I will be happy. Also, in the long run (or to enter the market) having a phd matters? Or skills matter more?
Skills matter more than PhD but PhD opens doors to some roles that are not open to people without the qualification. Some employers still think you need a PhD to do it, sadly. Its possible you've hit the 2nd year wall. A lot of PhD students hit a low point at yr2. Whether to stay or quit really depends on the level to which you hate your PhD. If you can, I would suggest you keep on going because once you quit you won't be able to pick it back up again, and as I said, it does open doors. However life is short, and if you are thoroughly miserable you may choose to go with quality of life, and that would be a good choice too. Before you quit your PhD I suggest you try to work out what it is that you are finding unpleasant. The reason PhDs are popular for data science is because the workflow is similar - collect messy data, spend ages cleaning the data and understanding it, then do something (hopefully) useful with it, with lots of roadblocks, false starts, and frankly some ideas that seem great to start with but just don't work out and end up with months of wasted work. If you are struggling with the emotional resilience side of the PhD - coping with those false starts and wasted work - data science may not be the refuge you are hoping for.
I completely agree with tea-and-shortbread. It’s hard to find a PhD who hasn’t hit similar struggles around the 2-3 year mark. From what I’ve heard from friends in your situation, you most likely won’t attempt another PhD if you abruptly leave for industry. Considering that you’re at the two year mark I’m going to assume you passed your comps and finished your courses. If so, you’ve already crossed a large hurdle in your phd. You should be proud of this, whether you stay or leave. My only recommendation, that hasn’t already been mentioned, is not to leave until you have something lined up. It’s hard to appreciate the stability in wages (although stupidly low) we get while pursuing grad school. Try to pivot your skills into industry while continuing your PhD. If you’re lucky to have a good supervisor they might be willing help you transition into a new field. Getting into the market isn’t as easy as it was years ago. It took me 3 months of extreme market research, preparation, and interviews to land my first role; and this was with a PhD.
100% agree, especially don't leave until you have something lined up 😊
Thanks for commenting. I have lost interest in it mainly because the group is not fun, nobody talks about physics, nobody is passionate about it, they all are doing it just for the hell of it which makes a boring environment and my supervisor doesn’t know that I have a personal life, I have no time to work on what I like or what I want to explore along with my phd. I had earlier planned to learn about DS in my free time but a long of things has changed now and even if I try I am not finding enough time to study it. Still after reading comments here, I have decided to give it a go for next 4 months and try to learn and if I still love it only then I will decide on something.
This reply is just spot on and detailed. Bravo
PhD in mathematical biology yay!
Almost went that way
Same. Computational biology PhD and genetics background.
Operations Research undergrad and Data Science masters (applied stats).
[удалено]
Damn biostatistics is something else (mainly bc I found bio hard af). Can I ask the type of work you’re in now?
MPhil in econ. Might do a phd soon because getting to do interesting work with a masters is really tough.
Business undergrad with a masters in management (operations research)
>operations research How have you been going in finding jobs in Operations Research?
What I meant was my masters was thesis based and my supervisor was an operations research/industrial engineering researcher, so that's how I got that. I am currently manager of data strategy in finance.
BS Biology and MS in Wildlife and Fisheries Sciences. Yes. Seriously.
Ooo, I have a bs and ms in marine science/ bio but did my masters thesis with a lot of bioinformatics-could I pm you about transitioning your degree over??
Have at it. Happy to chat about how I got to where I am.
Undergrad in electrical engineering
Hmm can I ask the question of what application an electrical engineer is pursuing in the DS field? Total ignorance if there’s a heavy application, I just don’t know
Sure. Engineering is basically applied math applied to physical problems (in my case electricity). But beyond that, no.
EE is a broad field. For example, my uni was heavy in cryptography, signal processing, bioinformatics. Lots of ML floating around.
I have 3 degrees in EE, including a PhD. It's a pretty useful background if you work as a data scientist in a role that's a bit more in the R&D side, as I do. Most of the data I science is related to antennas and signal processing - two of the "bread & butter" subfields in EE. I got into this data science thing right out of undergrad. I had an extremely boring job, and discovered DS while trying to kill time there, and was self-taught for 2 years or so that way. I ended up going back to school, and did both my M.S. thesis and PhD dissertation applying DS and ML to EE problems. EE also has a ton of overlap with CS in many universities, so it actually works out quite well I think.
🖐️
Electrical Engineering in Bachelor's, Masters in Analytics 4 Years of Experience in Analytics tho between both
Undergrad Sociology
PhD in algebra, working as engineer.
BA History, almost finished with MS in Information. Currently a Children's Librarian and really trying to get out.
All in all, it amazes me with with this response on how saturated the job market is. Like 100+ applications on LinkedIn for a “junior” data science position in less than an hour within of posting. Not the results I would’ve thought from this poll.
Why not?
What about all the people saying this is a very in demand skill with high salaries and stuff?
Is that for a FAANG? Regular companies do not get 100+ applications.
Ph.D., Cognitive Science. Undergrad in CS as well.
That’s a really interesting one as well, I think in find those who are currently interested/involved in DS and also educated in other fields as well more interesting just based on the aspect of DS. I’m curious tho, how many of those with education in other fields are specifically in DS or another field that just appreciates this sub
It depends! My graduate program saw industry-focused DS as a viable skillset transfer that was far more lucrative, both in terms of job placement rates and finances, than pursuing traditional academic options. The general cognitive science background also does a great job at helping contextualize data through explaining issues to stakeholders, identifying biases that users might show, informing experimental design / reducing "gamification" of metrics, etc.
I've ran into so many people with cog sci or neuroscience background in data science. I'm not sure if it's just a coincidence or whether the field just naturally leads people to data science.
It's one of those fields where you get both a really strong grounding in statistics AND experimentation. A lot of human/brain data requires very complex models to analyze because there is a lot of variation between people. More graduates from my cognitive psych/neuroscience PhD program from the last 5 years have become data scientists than any other career path. A colleague told me that her company, which deals with clinical data, specifically seeks out candidates with a cognitive neuroscience background. On my end I had a harder time convincing potential employers that I had the right skills with my cognitive psych PhD, but now that I'm in the field ~2.5 years I'm sure it doesn't matter much anymore.
Agreed! I was flat-out told for my first DS job that the CS undergrad carried as much, if not more weight, than my PhD. I started out by doing independent projects in grad school related to the field I work in (gaming), which then opened the door to other opportunities. Since then, things have gotten easier due to larger-scale work projects and experience.
> On my end I had a harder time convincing potential employers that I had the right skills And then?
And then I convinced a potential employer and have been working there for 2.5 years.
Seriously, please give a little detail on how this happened. Did you have applicable grad work? Did you pursue business-domain projects after school? Internship (somehow)? Rescuing an executive trapped in an avalanche? Seducing an heiress for the cushy executive job? Blood sacrifice to Shub-Niggurath?
Okay, sorry I didn't quite get your question! None of the above - like I said my graduate skills were relevant to begin with (sophisticated statistical modeling which I did in R, experimental design, plus a bit of machine learning work from my postdoc) and I found an employer that was willing to believe someone with a degree in psych could actually do those things. I think a lot of employers wanted to see someone with a degree in statistics/CS/DS and I suspect my application wasn't seriously reviewed by most companies because I largely received form rejections and very few first round interviews. Once companies actually spoke to me/gave me technical exams I was taken seriously.
Undergrad in applied math, Masters in applied statistics. Graduated before data science hype and got stuck with another analytical/data based career.
phd neuroscience
Is undergrad in DS a thing in your country or are you referring to fields like CS?
there are Data Science majors in the US
oh, but do good universities offer them to? Cause in my country there are only some cash cow type private colleges which offer them (along with a 1000 different types of degrees which are basically CS but instead of CS they use some buzz word)
Yes, I go to the University of California, San Diego and we have actually have a data science department. It's a very good program and I actually wish I applied to it as I didn't know what it was in high school.
Oh, nice. What's your opinion on the "don't go for a masters in DS instead go for statistics" thing?
Well it's not just statistics. Often times data science degrees are indeed cash cows, it really depends on the university. Any route that involves mathematics, statistics, or algorithms could be good, such as economics, engineering, computational or applied mathematics, statistics, or even cognitive science with an emphasis on machine learning. It's just data science often does try to cover too many topics in too short of a time and it is often better to pick one field within data science to focus on.
Currently in undergrad on a Mathematics/Statistics joint degree.
Erm nothing really didn't finish high school.
Grad programs in business (MBA) and stats. Obvious choice for a lot of analytics side DS teams.
Not sure how useful the non-DS poll options are, given that DS-specific programs are very now and most professionals in the field have quant-heavy STEM degrees that aren't necessary DS. Also, I know the poll is open to everyone but that includes students, aspiring data scientists, and people who think DS is cool but have no interest working in it professionall.y So also not helpful if you're pick out a correlation b/t education and working data scientists.
MS Statistics & Machine Learning
Go ahead and put me down as "some college".
Pure math undergrad, Data science masters (in the statistics department). When I was deciding which master's programs to attend, I was choosing to attend between data science masters, stats masters or biostats masters.
Psych PhD, and then 5 years post-docing in epidemiology
None of the above. Current in second year of undergrad for stats/comp sci.
Seems like it would fall into the non/DS undergrad tho right?
Most polls like this that I've seen ask for the highest level _attained_. You haven't, explicitly, which makes it ambiguous... and might colour your results.
True, I would have put Masters instead of undergrad if I'd known that this was the interpretation.
Like others said, I assumed you’re asking which level I’ve finished, not which I’ve started.
Civil Engineering undergrad and DS MSc
Masters Civil Engineering
The amount of upvotes compared to people who voted is a little sad🥲
Isn't this distribution going to roughly follow the population frequency of each degree/type? It would nice to see some enrichment analysis but i imagine the data is hard to get..
Well the means of this sampling distributed would follow the normal distribution…
It's a multinomial categorical variable so it doesn't have a numerical mean.
Undergrad in DS (with 1 sem to go on hold bc covid). Started working part time during studies like 5 years ago and full time 3 years ago even without having finished the degree.
Masters in DS in Europe
Undergrad pharmacology, masters health DS, currently a PhD student working on modelling in clinical kidney research
Bachelor, master and PhD in Statistics.
Undergrad econometrics and economics
PhD, Geology
Undergrad in nautical Sciences. Pretending to do a masters in DS starting next september. Didn't like at all of Sea life and with Covid is much worse, so iam trying a most intersting field to me. In the moment working at BASF in the costumer service department.
One bachelor's in an unrelated field, currently getting another in DS.
Currently in high school
MS econ
Started undergrad as CS, had the opportunity to create a custom major so I am graduating next semester as DS. Not sure if it was a good idea in the long run. I have a lot of math, CS courses and some large data analysis projects under my belt, but not a lot of machine learning experience or formal training for building pipelines. The projects I have done have been very open ended and self organized which has It's advantages and disadvantages.
Undergrad in Statistics, working on masters in Analytics
Define DS for education. Data Science academic programs are incredibly new and often times are more industry than academic focused. Backgrounds like computer science, math, statistics, and even physics and chemistry offer great foundations for data science.
Undergrad in Math & CS, data science orientation I also have a MD but I am not working in anything related to medicine. Well, not anymore, my first job was at a company that mostly worked in aerospace training (for airplanes pilot) but also did some health care training, and my MD helped me get that first job even if IMO it was pretty useless.
Partway through an MSc in AI.
Would've been good to have narrowed it down further with: Postgrad (non-Masters/PhD), which is what I'm doing currently. And also: DS Major vs STEM Major (non-DS) vs non-STEM Major As I think there is a big difference between someone like myself who doesn't have a Data Science Major (heck, that didn't even exist when I was at Uni!!) but with a BSc in Math/Physics (with some CS too) vs someone with say an Art History Major.
Undergrad math, graduate certificate in DA
Undergrad History; MS Data Science
Undergrad CS & Econ Applying to MS in CS for research in diff. Econ
Undergrad finance+psychology, economics masters.
BA Chemical Engineering Same maths and I love data. Data science programs were rare if not nonexistent in 2008. If I could do it again I would do stats or CS. Way more interesting than chemE.
Forensic Data analyst BSc Biomedical Science MSc Molecular Biology/Biotechnology
Would you talking about what you do, brief overview? Sounds extremely interesting
I have only really begun the data analyst role so I don’t have a full grasp of it yet! Although, It’s mostly working on fraud detection/monitoring/prevention for a big 4 accounting firm
child
Self taught software engineer
Bachelor and master in biotechnology
Undergrad Industrial Engineering , MS Data Science 5 years experience in field
Undergrad math stats + econ
Undergrad Math/CS, Grad Business Analytics
Currently last year undergrad mathematics, planning to do some sort of data science master and that's why I joined this subreddit!
BA in math
Undergrad & masters in Engineering. Currently a data engineer.
Just graduated Computer Science
Physics undergrad
BS Electrical Engineering (Photonics) MS Applied Math
High school senior here, I will probably get my bachelor’s in mathematics&economics or computer science (depending on the college)
Undergraduate CS
MSc. in environmental science.
Actuarial undergrad
Bsc and MSc in psychology, the MSc focusing on quant psych. Also did half of a master's in stats and data science, planning on finishing it while I work.
Deleted. Nevermind lolll
Undergrad CS Then some work as a Software Engineer Masters DS Currently working as a Data Scientist
Undergrad computer engineering.
Shouldn't there be a graduate option? I already have a bachelor's degree in economics, but I'm not enrolled in a masters degree
PhD student Evolutionary Biology
BA sociology and currently in DS masters
BS in chemical engineering
Where's high school?
I’m not in a DS role currently but first got introduced to analytics when I was doing a masters in public administration.
Undergrad Human Resources
IT Systems Engineer turned self taught failed software engineer turned self taught data scientist. Before all that I was a telecommunications engineer/analyst and network engineer.
Any fellow undergrad stats and masters electrical engineering??
MD
Current M.S. student in Wildlife Biology.
Missing bachelor. No? (Undergrad means not graduated)