I have a BA in economics/political science and managed to stumble into data science through some combination of self teaching and free/cheap online courses. The data science bootcamps through udemy and coursera were quite helpful for walking through python in a more specific way than a generalist programming class would. However I always viewed them more as a skill tutorial to get started than as a comprehensive career guide and I would never pay more than like $60 for them. When I see resumes with analytics masters degrees, I do have that reflexive sense that the job candidate overpaid for skills the could learn on the job or self teach.
However, I’m also a confident white dude who people frequently read as smarter than I actually am. Early in my career, people were willing to take chances on me and let me try things my resume at the time probably didn’t back up. Over time those chances and projects I wasn’t quite qualified for built up into a base of skills and experience I can now take to the job market to show my qualifications without talking about my degree at all. That’s not the case for everybody, and I think it’s harder to do in today’s job market than it was in the early days.
Not all that long ago, data teams were a rag tag bunch of nerds with a patchy old server inventing processes on the fly. There was no career path or formal academic training, and those teams were willing to take on new recruits who seemed smart and scrappy and reminded them a bit of themselves. My first mentor was a Russian Studies major who taught himself programming at the public library, my other colleagues came from across the academic spectrum and only one of us had an actual computer degree. Those early teams were fairly white, male, and nerdy and that shaped who reminded them of themselves and who might get that stretch opportunity.
I do think analytics degrees serve a purpose in allowing people who might not get those same early career opportunities to break into the field in a way they might not otherwise have access to. Several of my best colleagues have talked about the importance of that masters or pricey boot camp in allowing a career transition, often women or immigrants who just needed something to get through that initial resume screen. I think that’s especially important now as we’ve codified a bit more of the formal job skills and experiences we expect in data careers since those early days.
The moral of this story is twofold: First, these degrees do help people who might have a harder time breaking into a data careers, and I try to see their pursuit on a resume as a sign of ambition as opposed to a sign of falling for a scam (I do think they’re overpriced though). Second, even as our job responsibilities become more codified, we should try to take chances on people who are bright or scrappy and don’t have the exact technical skills yet, and we should take those chances on a broader swath of people. My best hire was a recent liberal arts major who taught herself a bit of data analysis at her last job but clearly didn’t know SQL all that well. I hired her anyways and she’s now 3 promotions into her data career and running circles around me from a technical standpoint.
I agree with you that the degrees are tricky for folks who don't have that access though. (This came up in another comment too: https://benn.substack.com/p/most-graduate-degrees-in-analytics/comment/101178946). I don't think most teams actually have much respect for the degrees, so it's tough. On one hand, they do help get a bit of a foot in the door, because you can get some early looks that you might not otherwise. On the other hand, I don't get the sense that a lot of teams see it that way, and think "we don't care about this degree, but understand that that may be the best shot this person has." They instead just think, "eh, we don't care about this degree." So it's kind of perverse thing, where the powers that be have not only made it hard to get into these jobs, but have also degraded the ways they get in. (And I guess you could say that articles like this don't help that, though I think it's worse if people aren't told that these degrees are disregarded than if we acknowledge what so many of this really are.)
On the third hand, I do think self-teaching and doing side projects is a pretty good (and accessible) way in too? It's not free, and it takes time, so you can't do it without effort, but you can do it with a lot less effort and money than it takes to get one of these degrees.
I think this is overstating the case by a lot. I work in an analytics department at a large company and most people (not me) have a masters in business or marketing analytics. I learned the same skills on the job but: a. I was opportunistic and lucky b. I still needed a data science bootcamp to learn SQL and Python. (Please don’t tell me I can learn on my own. I know my own limitations.) Most of the people I work with have foreign visas, can’t be out of work for significant periods of time, and need a dependable path.
That said, I think if there are industries where most people have these degrees, that's not necessarily a sign that they're useful. There are a lot of places where having an MBA is a prerequisite for the job, but I don't think that means MBAs are invaluable academic degrees. It just means that that's the mostly arbitrary gate that McKinsey set up, and now it's become an important cultural signal. So it's important, sure, but I'd argue it's more important as a social currency than anything all that "real."
I mean, define the word “scam.” If these degrees were useful steps to getting decent jobs (and visas), it’s hardly a scam, even if you don’t like the system.
> At best, pay-to-play master’s programs are ignored, and the degrees they offer are looked at as undifferentiated paper credentials. At worst, they’re viewed as a red flag, the dark mark of someone who proudly fell for a scam.
Just to add a real anecdote here - most resumes I reviewed that had a Masters of Data Science or Analytics from some random university almost never got to an interview. I never felt it was a red flag because they fell for a scam. It was a red flag because it signaled the opposite attributes I was looking for (but probably couldn't fully articulate at the time).
An applicant who has a Master of Data Science degree is probably less curious, has lower "agency", and overall lower adaptability than someone who has a different background and is moving into analytics. It's possible I missed some great folks who did have those attributes but were given some bad advice - but so it goes in hiring.
I can imagine how frustrating it is for people who are trying to break into analytics to hear that though. "I have the skills, the curiosity, the agency and I'm adaptable! But I don't have the title "data analyst" which makes it hard to get a job!" And yeah, I hear you. The hard to hear answer is you have to be creative about your career and figure out ways to get what you want with what you have. A masters in data analytics works for some people (maybe), but if you want to work in startups - just know it's a negative signal and act accordingly.
Yeah, that's probably a good way to put it. It doesn't differentiate folks in any way, which is part of why I think the schools are the ones to blame here, because they sell students on that differentiation. "This is a great thing, all these people will be impressed with your impressive credential!" And then Harvard or someone says it, so you think, yeah, of course they will, plus, it's Harvard. So you buy it and find out $50,000 later that no, nobody actually cares that much.
And yeah, the agency/creativity thing is tough. I have a friend who's a director / VP level at Google, and she was recently talking to someone who was a Level...5? and wanted to be a Level 6. (I don't know the exact numbers, but they were a senior IC and wanted to be staff or principal or whatever). And she asked my friend, "ok, I've done the things that people ask me to and they're all very good, and I'm not getting promoted, so what do I need to do now?" And the answer my friend gave was essentially, "That's a Level 5 question."
Which is kind of brutal and feels sort of unfair. But that's sort of also the point?
It’s hard not to notice the way this same air of robotic banality suffuses not only the sports-memoir genre but also the media rituals in which a top athlete is asked to describe the content or meaning of his technē. Turn on any post-contest TV interview: “Kenny, how did it feel to make that sensational game-winning shoestring catch in the end zone with absolutely no I mean zero time remaining on the clock?” “Well, Frank, I was just real pleased. I was real happy and also pleased. We’ve all worked hard and come a long way as a team, and it’s always a good feeling to be able to contribute.” “Mark, you've now homered in your last eight straight at-bats and lead both leagues in RBIs — any comment?” “Well, Bob, I’m just trying to take it one pitch at a time. I’ve been focusing on the fundamentals, you know, and trying to make a contribution, and all of us know we've got to take it one game at a time and hang in there and not look ahead and just basically do the best we can at all times.” This stuff is stupefying, and yet it also seems to be inevitable, maybe even necessary.
...
The real secret behind top athletes’ genius, then, may be as esoteric and obvious and dull and profound as silence itself. The real, many-veiled answer to the question of just what goes through a great player’s mind as he stands at the center of hostile crowd-noise and lines up the free-throw that will decide the game might well be: nothing at all.
How can great athletes shut off the Iago-like voice of the self? How can they bypass the head and simply and superbly act? How, at the critical moment, can they invoke for themselves a cliché as trite as “One ball at a time” or “Gotta concentrate here,” and mean it, and then do it? Maybe it’s because, for top athletes, clichés present themselves not as trite but simply as true.
...
It may well be that we spectators, who are not divinely gifted as athletes, are the only ones able truly to see, articulate, and animate the experience of the gift we are denied. And that those who receive and act out the gift of athletic genius must, perforce, be blind and dumb about it—and not because blindness and dumbness are the price of the gift, but because they are its essence.
Sure, if someone says, "What do we do next?" and the person in charge says, "oh man, I have no idea, got any ideas?," yeah, that's pretty bad. But there are stages you get to where the entire point is that you have to figure out the next step on your own. Like, that's why very successful people are very successful - they figured it out. You can help them ask questions and do the sort of coaching that helps them get better at thinking about how to figure it out, but "if I do what I'm told then I will do well" works only to a point.
I would see that as the exact opposite. That *is* mentorship - "if you want to reach a certain level of success, you have to figure out how to get there on your own." Sure, you can be a coach and give advice and all that; I'm not saying don't do those things. But there is a point at which nobody can tell you what you're supposed to do next, because the reason you get paid to do that next job is because you can figure it out without someone telling you.
Like, if the person said, "I want to be a great chef, what do I cook?," you can say think about this and that, but ultimately, the only correct answer is "You are not a great chef until you figure that out on your own."
Just finished my Spring Break and came back to see your article, thank you for writing it! I’m currently in my third quarter as an MS in Analytics student and wanted to share some personal thoughts and experiences here :) (p.s. I’ve read through all the comments below, so I’ll try not to repeat what’s already been said)
From my perspective, a helpful way to evaluate whether the MS in Analytics degree feels “scammy” or not is to segment students by their background. I’d say 3 distinct characteristics play a big role:
1. International vs. Domestic Students
[International Students (Scam Level: 0–5%)]
As you and others mentioned, many of us pursue this degree primarily to gain work VISA in the U.S., and the program effectively helps us achieve that. I think whether you'll feel scammy depends on WHAT you want to get out of the program. For me, I'm quite satisfied with the program bc:
1) We can get access to Business School resources (same as MBA students) like networking events and speaker sessions, all while paying half the tuition and spending less time in school. Even if we only benefit from ~20% of the MBA offerings due to class or schedule differences, that 20% still exceeded my expectations ;)
2) Coming from outside the U.S., I didn’t know much about us work culture. This program has helped me understand how to network, small talk, and build connections, all things I never learned back home and are very useful here
I’d say part of our cohort feels the same way I do, so the scam level should be low
[Domestic Students – Scam Level: 60–70%]
This is the group you described most in your article. I agree that many of my domestic classmates seem to feel the same way you do. They typically make up only 5–10% of the student population in most Analytics programs
2. Years of Full-Time Work Experience (note: International students often have more experience on average)
The more work experience you have, the less likely you are to feel scammed. This aligns with your point that companies care more about your prior work than your Analytics degree. Many of my classmates who came straight from undergrad find it much harder to land internships, while those with several years of experience find it easier, so the job success rate can feel a bit misleading if you don’t account for that factor.
3. Business vs. Engineering Undergrad Backgrounds
This one’s a bit more subjective, but worth mentioning. Most programs design their curriculum to teach technical skills (like programming and stats) with limited focus on business. As someone with a business background, I’ve personally learned a lot. But I sense that my engineering-background classmates don’t gain as much on the business side, which could leave some of them feeling shortchanged in terms of holistic development
Final Thoughts
Whether the program is a “scam” really depends on your background and what you expect to gain from the degree. Your arguments are valid, and I just wanted to add a few layers of nuance from my experience.
Personally, I’m happy with my choice so far. Curriculum-wise, we actually have some interesting courses, one of them is fully dedicated to prescriptive model, which I found super useful. As a former Product Manager, I used to only vaguely understand A/B testing, but now I feel much more confident designing and interpreting experiments
Thanks again for your thoughtful article, love how you spoke up about things that I believe more people should be aware of!
Thanks, I'm glad you liked it! And thanks for sharing all of this - the perspective of someone who's actually in one of these programs is probably better than some random guy yelling on the internet...
The big split between international and US students definitely makes a lot of sense. I did hear from some other people who saw the program as an MBA-ish type of degree, though the reviews I heard from folks who took that approach were somewhat mixed. Some felt it was like an MBA but they learned more hard skills (so good); some felt it was an MBA without the more universal corporate appeal (so bad). For the latter folks, it seems like they were disappointed by the job prospects that came after, though as you said, that could've been based on stuff like their prior work experience too.
That's an interesting dimension to all of this too. I think most folks I know who've gone through these programs did it right out of undergrad, and in a way that felt like a sales pitch: "It's a really competitive job market now, and an undergrad degree isn't enough, so come get this extra degree that will make you way more attractive!" And then they didn't really get much benefit from it. I suspect part of that is the program, but could also be related to what you said about wanting to learn more about A/B testing. If you have some work experience, you probably know what you want out of the program and can use it in a more targeted way, where I didn't get the impression that these folks felt that way. It was a kind of survey course for them, where they were there as much for the credential as the specific classes. And in the end, they got a credential that didn't get them very far.
3) The schools themselves are deceptive with numbers
1) feels irrelevant? Even if cobbled, the formula of "stats + programming" would act as a sufficient filter. Additionally the connection between class education and professional needs has always been tenuous. It isn't clear to me that it's not more tenuous than the outcomes for economics degrees, MBAs, or really any other field.
2) feels unlikely. Similar anecdotes exist for MBAs, but other anecdotes and stats clearly favor the degree. Obviously some gaming occurs, but the primary goal has typically been signalling whether it is IQ, conscientiousness, or ambition. In a lot of cases, even if analytics degrees were utterly irrelevant, they would still require some amount of quantitative or technical aptitude.
3) also feels likely to apply to the full business school as well, but also feels uncertain.
My gut guess is that most Analytics masters are just essentially a hyper-focused type of MIS degree with more focus on quantitative methods and less on enterprise systems. But I'd doubt "MIS Masters are scams" is not as compelling.
Ehh, I think I disagree with most of this. On 1), I'm not saying they weren't put together for analytics. I'm saying they were put together quickly, and using a lot of the classes and stuff that already existed. That could be fine, but it leaves out a lot of the "real-world" exposure to what most data jobs actually are. Which, for an academic degree, sure, that's the point - you learn the theory in school and the trade on the job. But these degrees kind of try to have to both ways, where they say they're all about career prep, but teach mostly tangential academic stuff instead.
On 2), that's simply not my experience. I've never once met a team that *favors* these degrees. People like "you got a stats degree from Berkeley" or something, but that's different (again, because I think it's read more as some IQ thing). I've never once heard of a team look at some 1-2 year degree from a business school analytics program and say, "yes, this is a sign of this person being very talented (or even ambitious, really). To the extent that they carry any weight, they might get you past an automated recruiting screen - which, for some folks, and particularly international students that are often unfairly overlooked, is really important. But the value of the degree is almost entirely from the loose network, and next to nothing from the education or the signal that you got into the program (in part because many of them have very high acceptance rates).
And on 3), yeah, absolutely, you can apply the same thing to MBAs, and I almost said that in the post. The one big difference is that there are "elite" MBA programs that are hard to get into. But again, that's as much about what kind of program you can get into as much as it's about what you learn.
Not only do you learn things you sort of need to unlearn - expectations are also totally misaligned
My most visceral example is the new hire data scientist who gets really frustrated that they have to wrangle data for months instead of “doing data science” (which in their mind basically means Kaggle competitions).
And that’s before you bring in the whole other beast of “hey maybe we should optimise for _business impact_ rather than “cool tech solution”, which even the non-Masters grads often need to learn/unlearn…
I’d go as far as to say that unlearning skills is easier in comparison to resetting expectations about what the job should be 🫠
Yeah, for sure, very much agree. The skills they teach aren't all bad, and some are probably pretty useful. But it's the mindset that's tough, where the programs frame the job as being capital-D Data Science, and then you show up and it's broken Adwords data and dashboard making. Which is, at best, a recipe for confusion, and at worst, ends up making everyone mad at each other.
I had a choice between capstone and thesis, and I was so burnt out from full time work and school at the same time, that a capstone was the quickest and easiest way out. It was a 30 page paper, but certainly not a thesis. I got promoted to manager of a team within 6 months of graduating and the masters (didn’t care where from) was a big selling point. I studied public administration and work for a heavily regulated industry, and not just pure data science, so that may be a difference here. My program was more into finance and program evaluation and descriptive statistics.
Huh, it's interesting that it was a big part of the hiring process. Did you get the sense that they were specifically looking for that, like some jobs has a rough requirement for you to have an MBA to get in the door? Or did they just see it as similar to having some other good work experience?
As someone with a master’s in data analytics who works in a highly credentialist industry (education) I think there are two good pathways for masters degrees: high-prestige and in stats or computer science or as cheap as possible and online. I did the second for $10k and it worked out for me but most people I work with came into the industry sideways. I think it would be a great pity if the specific degree becomes a requirement.
I work at the community college level, which means I am familiar with workforce degrees like the Associate of Applied Science or the Bachelor of Applied Science. I really feel that my degree was a Master of Applied Science but it did that well and gave me an overview of the tools I would need to actually do data as it exists at small community colleges which includes way fewer neural networks and way more telling people they are using the Student Information System incorrectly than most masters programs will tell you.
(I love my job and am good at it and am glad I paid 10k to help me get my foot in the door. If I had to go back I’d go all the way back and major in computer science as an undergraduate.)
Oh interesting. One potential angle to all of this, I suppose, is the degree becoming some sort of extension of an undergrad degree, where it's architected for people who didn't do CS or math in undergrad, but want to get into data jobs that are math and CS adjacent. So it would be less of a professional degree that teaches people about jobs, and more of an academic degree that catches people up who discovered what they wanted to do after college. That seems like it'd let schools do what they're good at, and would actually be a pretty valuable thing for the people who get.
I'd guess that doesn't make that much sense for the college though, who can probably make a lot more money from the professional degree, and - to your point - probably like the idea of degrees like these becoming somewhat of a requirement.
Thanks! And yeah, my conclusion about the Solow's paradox is a perhaps less eloquent version of yours - "As expected, IT did not reduce complexity; instead, it increased it" - and that it's Slack, because I hate it. https://benn.substack.com/p/the-product-is-the-process
I wish I had read this a year ago before embarking on a Master's Certificate in Data Technologies. =) I don't think I'll be pushing for the degree, though.
I applied for the program when I was feeling vulnerable, wanting an edge in finding a job. My hope was that it would signal my "always learning" trait, but I'm feeling a bit jaded by it now. Less expensive options out there.
Yeah, and that's another thing about these things: I know another program that markets heavily to recent grads who are still trying to figure out what to do, and they pitch it like, "It can't hurt to learn a few more things."
I hope that your program treated you better than that though, and that you at least came away with some good connections.
Mostly agree with this Benn and love your blog! I will say though, an analytics Masters is fantastic for international students especially when credentialing & signaling for US-based tech jobs, but you've already alluded to this. I also wonder if this still holds true with greater immigration scrutiny around H1-Bs.
For a lot of domestic students, an "applied data science" program would be better served by a stats/math program or frankly just a job.
Yeah, the international thing is tough. I'm not sure I'd agree that it's very good for signaling or credentialing - at least in Silicon Valley, people don't put much stock in most of these degrees, so it won't carry you very far. But they help get a very small toe in the door through the networks and career offices that they expose you to. It's not much, but it's a crack, which is something.
And I feel somewhat similarly about the applied stuff too, to be honest? Tech fetishizes math olympiad type stuff (which, again, I think is really because tech fetishizes some notion of IQ). Pure math and stats degrees can work in that way, because it seems "harder." Still, I'd guess even that is very school-specific, because people still don't really care about what you learned, and care more about what it means that you could get into or get through the program. (The caveat to that is for jobs that have more precise needs, like someone who's hired specifically to be a quantitative researcher for surveys or whatever.)
I mean, I have visited a couple MBA friends over the years, and it does seem like a pretty fun party?
Boot camps are....worse? Eeeh, it's a little tough. In theory, they probably work a little better: They are very practical skill focused; they're a lot cheaper; they take a bit more of an inclusive attitude, and follow more of a mantra that "anyone can learn to code if you put in a bit of time," which I largely agree with. But they tend to be more outright scams - or at least, outright monetization efforts for people with followings on the internet. Colleges are at least in part motivated by some higher calling of education. I think most bootcamps are motivated by someone trying to answer the question, "How do I extract money from my 50k Linkedin followers?" And that's how you seem to end up with stuff like Lambda School, which is an outright fraud.
(Another thing that some bootcamps do, which I think is smart, if not a little cynical, is they almost entirely teach people how to interview. Insight was like this. They didn't really teach all that much; they instead found high performing STEM academics who they knew could learn the job, and taught them how to find a job, interview, and connected them with hiring companies. It was a matchmaking service, not a makeover service, and it was the only bootcamp that seemed to really work. But it also wasn't really a bootcamp.)
Great point about the party - my perception is many of the elite MBA programs are just that - get to know other elites and the network / relationships will benefit you.
As far as influencer style bootcamps - I would image some have to be good and some are really terrible - and really impossible to know as the number of followers probably isn't related to bootcamp quality.
as far as "we will get you a job" style boot camps - 100% agree the successful ones are the ones that teach all the right skills to get a job. Almost like SAT prep.
yeah, "party with rich and influential people" isn't exactly the most noble sell, but it's also a pretty good sell...
And yeah, I think I agree about the bootcamps, though off the top of my head, I'm not sure I can name any I'd fully recommend. (Which doesn't mean they don't exist; it just means I know of a few that are scammy, and don't know of any that aren't. I'd imagine some have to be good though, and I just don't know them.)
The Richard Feynman interview is a classic. I think Einstein said “things should be simplified as much as possible, and no more.” Maybe this is what Feynman was saying too.
See, when Feynman does it, everyone says he's a genius, and when I do it, everyone is like, "god, just answer the question already." Just because he won a Nobel prize and invented half of physics or whatever, gah.
I have mixed feelings about these degrees.
I have a BA in economics/political science and managed to stumble into data science through some combination of self teaching and free/cheap online courses. The data science bootcamps through udemy and coursera were quite helpful for walking through python in a more specific way than a generalist programming class would. However I always viewed them more as a skill tutorial to get started than as a comprehensive career guide and I would never pay more than like $60 for them. When I see resumes with analytics masters degrees, I do have that reflexive sense that the job candidate overpaid for skills the could learn on the job or self teach.
However, I’m also a confident white dude who people frequently read as smarter than I actually am. Early in my career, people were willing to take chances on me and let me try things my resume at the time probably didn’t back up. Over time those chances and projects I wasn’t quite qualified for built up into a base of skills and experience I can now take to the job market to show my qualifications without talking about my degree at all. That’s not the case for everybody, and I think it’s harder to do in today’s job market than it was in the early days.
Not all that long ago, data teams were a rag tag bunch of nerds with a patchy old server inventing processes on the fly. There was no career path or formal academic training, and those teams were willing to take on new recruits who seemed smart and scrappy and reminded them a bit of themselves. My first mentor was a Russian Studies major who taught himself programming at the public library, my other colleagues came from across the academic spectrum and only one of us had an actual computer degree. Those early teams were fairly white, male, and nerdy and that shaped who reminded them of themselves and who might get that stretch opportunity.
I do think analytics degrees serve a purpose in allowing people who might not get those same early career opportunities to break into the field in a way they might not otherwise have access to. Several of my best colleagues have talked about the importance of that masters or pricey boot camp in allowing a career transition, often women or immigrants who just needed something to get through that initial resume screen. I think that’s especially important now as we’ve codified a bit more of the formal job skills and experiences we expect in data careers since those early days.
The moral of this story is twofold: First, these degrees do help people who might have a harder time breaking into a data careers, and I try to see their pursuit on a resume as a sign of ambition as opposed to a sign of falling for a scam (I do think they’re overpriced though). Second, even as our job responsibilities become more codified, we should try to take chances on people who are bright or scrappy and don’t have the exact technical skills yet, and we should take those chances on a broader swath of people. My best hire was a recent liberal arts major who taught herself a bit of data analysis at her last job but clearly didn’t know SQL all that well. I hired her anyways and she’s now 3 promotions into her data career and running circles around me from a technical standpoint.
Yeah, I have a similar background, and though I never did any bootcamps, 1) mostly learned on the job, and 2) was able to learn on the job, because I eventually found a way into a tech company via some (light) nepotism. (https://benn.substack.com/p/analytics-is-at-a-crossroads?utm_source=publication-search#:~:text=I%20was%20nearly,been%20very%20different)
I agree with you that the degrees are tricky for folks who don't have that access though. (This came up in another comment too: https://benn.substack.com/p/most-graduate-degrees-in-analytics/comment/101178946). I don't think most teams actually have much respect for the degrees, so it's tough. On one hand, they do help get a bit of a foot in the door, because you can get some early looks that you might not otherwise. On the other hand, I don't get the sense that a lot of teams see it that way, and think "we don't care about this degree, but understand that that may be the best shot this person has." They instead just think, "eh, we don't care about this degree." So it's kind of perverse thing, where the powers that be have not only made it hard to get into these jobs, but have also degraded the ways they get in. (And I guess you could say that articles like this don't help that, though I think it's worse if people aren't told that these degrees are disregarded than if we acknowledge what so many of this really are.)
On the third hand, I do think self-teaching and doing side projects is a pretty good (and accessible) way in too? It's not free, and it takes time, so you can't do it without effort, but you can do it with a lot less effort and money than it takes to get one of these degrees.
I think this is overstating the case by a lot. I work in an analytics department at a large company and most people (not me) have a masters in business or marketing analytics. I learned the same skills on the job but: a. I was opportunistic and lucky b. I still needed a data science bootcamp to learn SQL and Python. (Please don’t tell me I can learn on my own. I know my own limitations.) Most of the people I work with have foreign visas, can’t be out of work for significant periods of time, and need a dependable path.
yeah, the international part is messy: https://benn.substack.com/p/most-graduate-degrees-in-analytics/comment/101230800. And I suspect it's fair that these sorts of degrees are viewed differently in big companies than they are in tech, which is a little bit allergic to certain types of credentialing.
That said, I think if there are industries where most people have these degrees, that's not necessarily a sign that they're useful. There are a lot of places where having an MBA is a prerequisite for the job, but I don't think that means MBAs are invaluable academic degrees. It just means that that's the mostly arbitrary gate that McKinsey set up, and now it's become an important cultural signal. So it's important, sure, but I'd argue it's more important as a social currency than anything all that "real."
I mean, define the word “scam.” If these degrees were useful steps to getting decent jobs (and visas), it’s hardly a scam, even if you don’t like the system.
i apologize because this is the most repulsive thing i've ever done, but i'm going to post a link to a linkedin post: https://www.linkedin.com/feed/update/urn:li:activity:7307792882663362561/
> At best, pay-to-play master’s programs are ignored, and the degrees they offer are looked at as undifferentiated paper credentials. At worst, they’re viewed as a red flag, the dark mark of someone who proudly fell for a scam.
Just to add a real anecdote here - most resumes I reviewed that had a Masters of Data Science or Analytics from some random university almost never got to an interview. I never felt it was a red flag because they fell for a scam. It was a red flag because it signaled the opposite attributes I was looking for (but probably couldn't fully articulate at the time).
An applicant who has a Master of Data Science degree is probably less curious, has lower "agency", and overall lower adaptability than someone who has a different background and is moving into analytics. It's possible I missed some great folks who did have those attributes but were given some bad advice - but so it goes in hiring.
I can imagine how frustrating it is for people who are trying to break into analytics to hear that though. "I have the skills, the curiosity, the agency and I'm adaptable! But I don't have the title "data analyst" which makes it hard to get a job!" And yeah, I hear you. The hard to hear answer is you have to be creative about your career and figure out ways to get what you want with what you have. A masters in data analytics works for some people (maybe), but if you want to work in startups - just know it's a negative signal and act accordingly.
Enjoyed the write-up, Benn. Thanks for sharing!
Yeah, that's probably a good way to put it. It doesn't differentiate folks in any way, which is part of why I think the schools are the ones to blame here, because they sell students on that differentiation. "This is a great thing, all these people will be impressed with your impressive credential!" And then Harvard or someone says it, so you think, yeah, of course they will, plus, it's Harvard. So you buy it and find out $50,000 later that no, nobody actually cares that much.
And yeah, the agency/creativity thing is tough. I have a friend who's a director / VP level at Google, and she was recently talking to someone who was a Level...5? and wanted to be a Level 6. (I don't know the exact numbers, but they were a senior IC and wanted to be staff or principal or whatever). And she asked my friend, "ok, I've done the things that people ask me to and they're all very good, and I'm not getting promoted, so what do I need to do now?" And the answer my friend gave was essentially, "That's a Level 5 question."
Which is kind of brutal and feels sort of unfair. But that's sort of also the point?
> That's a Level 5 question
Brutal indeed. This reminds me of Cedric's tweet (RT of Visakan) a few months ago on thresholds https://x.com/ejames_c/status/1862023863972044899
This reminds of the last couple pages of this David Foster Wallace essay, which I think is one of the greats about this sort of thing:
https://bpb-us-e1.wpmucdn.com/sites.psu.edu/dist/7/59784/files/2016/08/DFW-How-Tracy-Austin-Broke-My-Heart-1994-1lctx91.pdf
--
It’s hard not to notice the way this same air of robotic banality suffuses not only the sports-memoir genre but also the media rituals in which a top athlete is asked to describe the content or meaning of his technē. Turn on any post-contest TV interview: “Kenny, how did it feel to make that sensational game-winning shoestring catch in the end zone with absolutely no I mean zero time remaining on the clock?” “Well, Frank, I was just real pleased. I was real happy and also pleased. We’ve all worked hard and come a long way as a team, and it’s always a good feeling to be able to contribute.” “Mark, you've now homered in your last eight straight at-bats and lead both leagues in RBIs — any comment?” “Well, Bob, I’m just trying to take it one pitch at a time. I’ve been focusing on the fundamentals, you know, and trying to make a contribution, and all of us know we've got to take it one game at a time and hang in there and not look ahead and just basically do the best we can at all times.” This stuff is stupefying, and yet it also seems to be inevitable, maybe even necessary.
...
The real secret behind top athletes’ genius, then, may be as esoteric and obvious and dull and profound as silence itself. The real, many-veiled answer to the question of just what goes through a great player’s mind as he stands at the center of hostile crowd-noise and lines up the free-throw that will decide the game might well be: nothing at all.
How can great athletes shut off the Iago-like voice of the self? How can they bypass the head and simply and superbly act? How, at the critical moment, can they invoke for themselves a cliché as trite as “One ball at a time” or “Gotta concentrate here,” and mean it, and then do it? Maybe it’s because, for top athletes, clichés present themselves not as trite but simply as true.
...
It may well be that we spectators, who are not divinely gifted as athletes, are the only ones able truly to see, articulate, and animate the experience of the gift we are denied. And that those who receive and act out the gift of athletic genius must, perforce, be blind and dumb about it—and not because blindness and dumbness are the price of the gift, but because they are its essence.
Sure, if someone says, "What do we do next?" and the person in charge says, "oh man, I have no idea, got any ideas?," yeah, that's pretty bad. But there are stages you get to where the entire point is that you have to figure out the next step on your own. Like, that's why very successful people are very successful - they figured it out. You can help them ask questions and do the sort of coaching that helps them get better at thinking about how to figure it out, but "if I do what I'm told then I will do well" works only to a point.
I would see that as the exact opposite. That *is* mentorship - "if you want to reach a certain level of success, you have to figure out how to get there on your own." Sure, you can be a coach and give advice and all that; I'm not saying don't do those things. But there is a point at which nobody can tell you what you're supposed to do next, because the reason you get paid to do that next job is because you can figure it out without someone telling you.
Like, if the person said, "I want to be a great chef, what do I cook?," you can say think about this and that, but ultimately, the only correct answer is "You are not a great chef until you figure that out on your own."
Just finished my Spring Break and came back to see your article, thank you for writing it! I’m currently in my third quarter as an MS in Analytics student and wanted to share some personal thoughts and experiences here :) (p.s. I’ve read through all the comments below, so I’ll try not to repeat what’s already been said)
From my perspective, a helpful way to evaluate whether the MS in Analytics degree feels “scammy” or not is to segment students by their background. I’d say 3 distinct characteristics play a big role:
1. International vs. Domestic Students
[International Students (Scam Level: 0–5%)]
As you and others mentioned, many of us pursue this degree primarily to gain work VISA in the U.S., and the program effectively helps us achieve that. I think whether you'll feel scammy depends on WHAT you want to get out of the program. For me, I'm quite satisfied with the program bc:
1) We can get access to Business School resources (same as MBA students) like networking events and speaker sessions, all while paying half the tuition and spending less time in school. Even if we only benefit from ~20% of the MBA offerings due to class or schedule differences, that 20% still exceeded my expectations ;)
2) Coming from outside the U.S., I didn’t know much about us work culture. This program has helped me understand how to network, small talk, and build connections, all things I never learned back home and are very useful here
I’d say part of our cohort feels the same way I do, so the scam level should be low
[Domestic Students – Scam Level: 60–70%]
This is the group you described most in your article. I agree that many of my domestic classmates seem to feel the same way you do. They typically make up only 5–10% of the student population in most Analytics programs
2. Years of Full-Time Work Experience (note: International students often have more experience on average)
The more work experience you have, the less likely you are to feel scammed. This aligns with your point that companies care more about your prior work than your Analytics degree. Many of my classmates who came straight from undergrad find it much harder to land internships, while those with several years of experience find it easier, so the job success rate can feel a bit misleading if you don’t account for that factor.
3. Business vs. Engineering Undergrad Backgrounds
This one’s a bit more subjective, but worth mentioning. Most programs design their curriculum to teach technical skills (like programming and stats) with limited focus on business. As someone with a business background, I’ve personally learned a lot. But I sense that my engineering-background classmates don’t gain as much on the business side, which could leave some of them feeling shortchanged in terms of holistic development
Final Thoughts
Whether the program is a “scam” really depends on your background and what you expect to gain from the degree. Your arguments are valid, and I just wanted to add a few layers of nuance from my experience.
Personally, I’m happy with my choice so far. Curriculum-wise, we actually have some interesting courses, one of them is fully dedicated to prescriptive model, which I found super useful. As a former Product Manager, I used to only vaguely understand A/B testing, but now I feel much more confident designing and interpreting experiments
Thanks again for your thoughtful article, love how you spoke up about things that I believe more people should be aware of!
Thanks, I'm glad you liked it! And thanks for sharing all of this - the perspective of someone who's actually in one of these programs is probably better than some random guy yelling on the internet...
The big split between international and US students definitely makes a lot of sense. I did hear from some other people who saw the program as an MBA-ish type of degree, though the reviews I heard from folks who took that approach were somewhat mixed. Some felt it was like an MBA but they learned more hard skills (so good); some felt it was an MBA without the more universal corporate appeal (so bad). For the latter folks, it seems like they were disappointed by the job prospects that came after, though as you said, that could've been based on stuff like their prior work experience too.
That's an interesting dimension to all of this too. I think most folks I know who've gone through these programs did it right out of undergrad, and in a way that felt like a sales pitch: "It's a really competitive job market now, and an undergrad degree isn't enough, so come get this extra degree that will make you way more attractive!" And then they didn't really get much benefit from it. I suspect part of that is the program, but could also be related to what you said about wanting to learn more about A/B testing. If you have some work experience, you probably know what you want out of the program and can use it in a more targeted way, where I didn't get the impression that these folks felt that way. It was a kind of survey course for them, where they were there as much for the credential as the specific classes. And in the end, they got a credential that didn't get them very far.
I feel somewhat confused at the arguments:
1) The degrees weren't put together for analytics
2) The market (anecdotally) rejects these degrees
3) The schools themselves are deceptive with numbers
1) feels irrelevant? Even if cobbled, the formula of "stats + programming" would act as a sufficient filter. Additionally the connection between class education and professional needs has always been tenuous. It isn't clear to me that it's not more tenuous than the outcomes for economics degrees, MBAs, or really any other field.
2) feels unlikely. Similar anecdotes exist for MBAs, but other anecdotes and stats clearly favor the degree. Obviously some gaming occurs, but the primary goal has typically been signalling whether it is IQ, conscientiousness, or ambition. In a lot of cases, even if analytics degrees were utterly irrelevant, they would still require some amount of quantitative or technical aptitude.
3) also feels likely to apply to the full business school as well, but also feels uncertain.
My gut guess is that most Analytics masters are just essentially a hyper-focused type of MIS degree with more focus on quantitative methods and less on enterprise systems. But I'd doubt "MIS Masters are scams" is not as compelling.
Ehh, I think I disagree with most of this. On 1), I'm not saying they weren't put together for analytics. I'm saying they were put together quickly, and using a lot of the classes and stuff that already existed. That could be fine, but it leaves out a lot of the "real-world" exposure to what most data jobs actually are. Which, for an academic degree, sure, that's the point - you learn the theory in school and the trade on the job. But these degrees kind of try to have to both ways, where they say they're all about career prep, but teach mostly tangential academic stuff instead.
On 2), that's simply not my experience. I've never once met a team that *favors* these degrees. People like "you got a stats degree from Berkeley" or something, but that's different (again, because I think it's read more as some IQ thing). I've never once heard of a team look at some 1-2 year degree from a business school analytics program and say, "yes, this is a sign of this person being very talented (or even ambitious, really). To the extent that they carry any weight, they might get you past an automated recruiting screen - which, for some folks, and particularly international students that are often unfairly overlooked, is really important. But the value of the degree is almost entirely from the loose network, and next to nothing from the education or the signal that you got into the program (in part because many of them have very high acceptance rates).
And on 3), yeah, absolutely, you can apply the same thing to MBAs, and I almost said that in the post. The one big difference is that there are "elite" MBA programs that are hard to get into. But again, that's as much about what kind of program you can get into as much as it's about what you learn.
💯💯💯
Not only do you learn things you sort of need to unlearn - expectations are also totally misaligned
My most visceral example is the new hire data scientist who gets really frustrated that they have to wrangle data for months instead of “doing data science” (which in their mind basically means Kaggle competitions).
And that’s before you bring in the whole other beast of “hey maybe we should optimise for _business impact_ rather than “cool tech solution”, which even the non-Masters grads often need to learn/unlearn…
I’d go as far as to say that unlearning skills is easier in comparison to resetting expectations about what the job should be 🫠
Yeah, for sure, very much agree. The skills they teach aren't all bad, and some are probably pretty useful. But it's the mindset that's tough, where the programs frame the job as being capital-D Data Science, and then you show up and it's broken Adwords data and dashboard making. Which is, at best, a recipe for confusion, and at worst, ends up making everyone mad at each other.
Brilliant article...and love the opening "it depends" 😂
Thanks! And another reader sent me this link: https://www.kellystanze.com/shop/p/it-depends-seo-humor-unisex-short-sleeve-t-shirt
🤣🤣🤣cool
I had a choice between capstone and thesis, and I was so burnt out from full time work and school at the same time, that a capstone was the quickest and easiest way out. It was a 30 page paper, but certainly not a thesis. I got promoted to manager of a team within 6 months of graduating and the masters (didn’t care where from) was a big selling point. I studied public administration and work for a heavily regulated industry, and not just pure data science, so that may be a difference here. My program was more into finance and program evaluation and descriptive statistics.
Huh, it's interesting that it was a big part of the hiring process. Did you get the sense that they were specifically looking for that, like some jobs has a rough requirement for you to have an MBA to get in the door? Or did they just see it as similar to having some other good work experience?
As someone with a master’s in data analytics who works in a highly credentialist industry (education) I think there are two good pathways for masters degrees: high-prestige and in stats or computer science or as cheap as possible and online. I did the second for $10k and it worked out for me but most people I work with came into the industry sideways. I think it would be a great pity if the specific degree becomes a requirement.
I work at the community college level, which means I am familiar with workforce degrees like the Associate of Applied Science or the Bachelor of Applied Science. I really feel that my degree was a Master of Applied Science but it did that well and gave me an overview of the tools I would need to actually do data as it exists at small community colleges which includes way fewer neural networks and way more telling people they are using the Student Information System incorrectly than most masters programs will tell you.
(I love my job and am good at it and am glad I paid 10k to help me get my foot in the door. If I had to go back I’d go all the way back and major in computer science as an undergraduate.)
Oh interesting. One potential angle to all of this, I suppose, is the degree becoming some sort of extension of an undergrad degree, where it's architected for people who didn't do CS or math in undergrad, but want to get into data jobs that are math and CS adjacent. So it would be less of a professional degree that teaches people about jobs, and more of an academic degree that catches people up who discovered what they wanted to do after college. That seems like it'd let schools do what they're good at, and would actually be a pretty valuable thing for the people who get.
I'd guess that doesn't make that much sense for the college though, who can probably make a lot more money from the professional degree, and - to your point - probably like the idea of degrees like these becoming somewhat of a requirement.
I completely agree, as always. I read you years ago with another profile, and finally, I wrote a piece about data from a different perspective: https://0utcast.substack.com/p/the-data-deluge-unraveling-the-productivity. Thank you for the insight you have given me so many times.
Thanks! And yeah, my conclusion about the Solow's paradox is a perhaps less eloquent version of yours - "As expected, IT did not reduce complexity; instead, it increased it" - and that it's Slack, because I hate it. https://benn.substack.com/p/the-product-is-the-process
Sexiest?
Data science is “the sexist job of the 21st century,” said the Harvard Business Review, famously
Wow, I swear, this is at least the third time I've done this. (Thanks, and fixed!)
I wish I had read this a year ago before embarking on a Master's Certificate in Data Technologies. =) I don't think I'll be pushing for the degree, though.
I applied for the program when I was feeling vulnerable, wanting an edge in finding a job. My hope was that it would signal my "always learning" trait, but I'm feeling a bit jaded by it now. Less expensive options out there.
Yeah, and that's another thing about these things: I know another program that markets heavily to recent grads who are still trying to figure out what to do, and they pitch it like, "It can't hurt to learn a few more things."
I hope that your program treated you better than that though, and that you at least came away with some good connections.
Mostly agree with this Benn and love your blog! I will say though, an analytics Masters is fantastic for international students especially when credentialing & signaling for US-based tech jobs, but you've already alluded to this. I also wonder if this still holds true with greater immigration scrutiny around H1-Bs.
For a lot of domestic students, an "applied data science" program would be better served by a stats/math program or frankly just a job.
Yeah, the international thing is tough. I'm not sure I'd agree that it's very good for signaling or credentialing - at least in Silicon Valley, people don't put much stock in most of these degrees, so it won't carry you very far. But they help get a very small toe in the door through the networks and career offices that they expose you to. It's not much, but it's a crack, which is something.
And I feel somewhat similarly about the applied stuff too, to be honest? Tech fetishizes math olympiad type stuff (which, again, I think is really because tech fetishizes some notion of IQ). Pure math and stats degrees can work in that way, because it seems "harder." Still, I'd guess even that is very school-specific, because people still don't really care about what you learned, and care more about what it means that you could get into or get through the program. (The caveat to that is for jobs that have more precise needs, like someone who's hired specifically to be a quantitative researcher for surveys or whatever.)
(And also, thanks, and hope you've been good!)
Appreciate the response—great writing as always Benn! Love the blog.
So, are you going back to school for a master's, then? :-)
Also - What's your opinion on analytics boot camps?
I mean, I have visited a couple MBA friends over the years, and it does seem like a pretty fun party?
Boot camps are....worse? Eeeh, it's a little tough. In theory, they probably work a little better: They are very practical skill focused; they're a lot cheaper; they take a bit more of an inclusive attitude, and follow more of a mantra that "anyone can learn to code if you put in a bit of time," which I largely agree with. But they tend to be more outright scams - or at least, outright monetization efforts for people with followings on the internet. Colleges are at least in part motivated by some higher calling of education. I think most bootcamps are motivated by someone trying to answer the question, "How do I extract money from my 50k Linkedin followers?" And that's how you seem to end up with stuff like Lambda School, which is an outright fraud.
(Another thing that some bootcamps do, which I think is smart, if not a little cynical, is they almost entirely teach people how to interview. Insight was like this. They didn't really teach all that much; they instead found high performing STEM academics who they knew could learn the job, and taught them how to find a job, interview, and connected them with hiring companies. It was a matchmaking service, not a makeover service, and it was the only bootcamp that seemed to really work. But it also wasn't really a bootcamp.)
Great point about the party - my perception is many of the elite MBA programs are just that - get to know other elites and the network / relationships will benefit you.
As far as influencer style bootcamps - I would image some have to be good and some are really terrible - and really impossible to know as the number of followers probably isn't related to bootcamp quality.
as far as "we will get you a job" style boot camps - 100% agree the successful ones are the ones that teach all the right skills to get a job. Almost like SAT prep.
yeah, "party with rich and influential people" isn't exactly the most noble sell, but it's also a pretty good sell...
And yeah, I think I agree about the bootcamps, though off the top of my head, I'm not sure I can name any I'd fully recommend. (Which doesn't mean they don't exist; it just means I know of a few that are scammy, and don't know of any that aren't. I'd imagine some have to be good though, and I just don't know them.)
Yup - that seems right. I know some good ones that are local/small.
The Richard Feynman interview is a classic. I think Einstein said “things should be simplified as much as possible, and no more.” Maybe this is what Feynman was saying too.
See, when Feynman does it, everyone says he's a genius, and when I do it, everyone is like, "god, just answer the question already." Just because he won a Nobel prize and invented half of physics or whatever, gah.