Seriously, why not Data Science instead of IB/PE?
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A data scientist makes 41K pounds for 40 hours of work, while a banker make 58K pounds on average in London for 80 hours of work (source: payscale). This means that a data scientist makes 20 pounds an hour, while a banker makes 14 pounds an hour
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Data Scientists arguably have a better chance of starting their own business as they 1) have expertise in a new technology that has lots of potential, 2) have a lot more free time to spend on side projects. Actually, let me rephrase 2) - a Data scientist has time for side projects, while a banker barely even has time to sleep.
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Even if you get into PE, most of your time goes to working for someone else, instead of building your own thing. You could theoretically buy a business after a few years in or try launching a business after you leave (since you will not have time for side gigs while working there), but realistically, how common is that? I mean you don't really make fuck you money to spend on buying a business until you are at least 7-10 years in.
So, why is everyone here chasing IB/PE instead of Data Science? What am I missing?
Because you need to be actually smart to succeed as a data scientist
And most kids in IB, PE, big law, etc are there because they are risk averse af and love prestige and have no desire to start their own businesses
I dont think its risk aversion to be honest. Launching a side project nowadays (if its software) doesn't require that much investment. Instead of spending that additional 40 hours a week slaving away for a bank, one could work on their own project. I mean you are giving up some money to pursue that project, but looking at it at another angle, you could technically take up a second job and would still be better off than in banking.
As for being smart: since most people that get into IBs had to perform well in school/are high achievers, I cant imagine this is the case either.
THE EARNINGS POTENTIAL. To me it seems like beginning in investment banking has a far higher earnings potential in the long run and if done correctly you could be in a relationship role later in life making a larger some of money than you could be in a hired data science roll. That being said, one needs to consider the lifestyle of each and they differ greatly. A data scientist will probably never be given real power within a corporation, but outside a corporation their ability to create a start up or their own IP is infinite. You could hit the jackpot if you focus on creating your own profitable IP and have a pretty stress free life after doing so. On the banking end, stress will always be part of the job. The question is can you manage it to the point where the number you were aiming for is achieved. The answer to that question is usually no, seeing that most people dont have a number at expectations increase as lifestyles are upgraded.
datascienceoasis doesn't have the same ring
Ill give you that, +1
The value in finance is learning how to manage your money well and multiply it. Say you have a decent exit, then what?
Also ex-IB/PE guys make excellent entrepreneurs. I love working with them far more than any other group. FWIW one of my ex founders was one of the first employees at a large tech co with a background in data science. Smart? Yes. Good investor? Nope.
Recurring theme with engineers is how horrible they are with people/soft skills. Once you get out of entry level grinding, your soft skills are what make $$$.
This isn’t a reason people here shouldn’t go into data science. seems like a fallacy, data scientists don’t inherently have bad people skills
Why get a job when you can just become a tiktok/onlyfans star? The comparisons you make are even more nonsensical than the monthly SWE vs IB post
yes many professions earn more hourly than bankers, few give you nearly as much nationality into even higher paying professions
I'm not even gonna address this because data science != entrepreneurship, google hires THOUSANDS of swe interns a year, how many go on to found successful startups?
I don't even know what your saying in point 3 but it does exist and it's called a search fund
"yes many professions earn more hourly than bankers, few give you nearly as much nationality into even higher paying professions" * Again, pay is just part of it. I believe that given the same ambitions, you have more earnings potential as a SWE/Data Scientist
I'm not even gonna address this because data science != entrepreneurship, google hires THOUSANDS of swe interns a year, how many go on to found successful startups?
I don't even know what your saying in point 3 but it does exist and it's called a search fund * Exactly how are you planning to launch a search fund without 10-15+ year experience in PE and a perfect track record? I'd argue that its even harder to launch than a regular startup
Math major?
You are missing the fact that human beings are not robots. People have different ambitions and desires. Not everyone wants to start a business. You should be if not passionate at least interested in the career you are pursuing. This reasoning could be done when comparing HF to MF, comparing two banks, not between Data Science and IB/PE, that are completely different animals. If you cannot understand this basic principle about human behaviour, and pretend to compare with a pros and cons list this two lifestyles as two products, than you certainly don't have a clue about what you want to do with your life, and you are just scared because you think there's something you are missing that other people are not. In my opinion choosing a career on numbers is the recipe for unhappiness.
Using payscale as your source for comp invalidates the credibility of your post. You need to add in bonuses if you really want to compare comps. Bankers undoubtedly make more at the entry level.
Ok, tell me a good source then. The comments on WSO telling kids that you will be making 200k starting out? In NYC maybe, but if youre expecting that kind of pay in London, youre in for a surprise. One of my friends just started at Rothschild as an M&A intern and he will be making 40-50k pounds, no bonus, in London.
Interns don't get bonuses.
Can guarantee first year comp will be over 75k all in.
Also have a look at this; https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahU…
Why data science for 40 hrs? There are many other 40 hr jobs. F500 would be more useful for starting a business imo.
Maybe I should have written CS, but the reason I chose data science is that currently it seems to be one the best segments to launch a business in.
This might come as a surprise, but some people decide based on what they're interested in, not where you make the most money out of uni
Pay was just one part of my post. The biggest argument for Data Science I think is that 1) you have a skill in an area which is currently a hotbed for entrepreneurship and 2) you actually have enough free time to act on that skill.
Not many people can pull of launching a business on the side while working 80+ hours a week in IB/PE. I mean they could take a jump and pursue entrepreneurship full time but 1) that is a LOT of risk (arent IB people supposed to be risk averse?) and 2) what actual skill do you learn in IB/PE that you could create a business based on? Decorating ppts/financial modelling? Yes, you could start a pizza shop etc., but you could do that eithout IB too. Launching your own fund? Good luck with that without 10+ years of good track record. Meanwhile with data science no one gives a shit about prestige and the opportunities are endless (if youve got some business accumen).
Not trying to shit on IB/PE as I work in this area too, but Im just trying to challenge this finance above all mentality, as right now it seems to me that one would be set for success a lot bettter in tech.
I could make the same comment about developing a skill. If you don't give a fuck about that skill or area of work, why would you ever pursue it? Chances are you wouldn't become successful anyway if that's the case.
There are a lot of people who don't want to be entrepreneurs...
Fuck off and get back to work
This whole post was made by a kid who didn't get into IB and is trying to convince people that he's still ahead.
I mean, you think data science is better for entrepreneurship than IB? Maybe if you want to start a company that makes adware. But that's about it.
imagine having a god complex about IB. you're worked as a monkey and don't do any intellectual work. data science confers genuine ability and has way more parallels to entrepreneurship than IB. what the fk is wrong with this website
I have a god complex? I'm not on Blind rambling about how I think banking is better than SWE and using shoddy information to do it. I couldn't care less as to what you deem to be intellectual, understanding the way a business, capital, and industries function is always going to be appreciated more.
What kind of flex is "incoming data analyst"?
I’m not really sure what this has turned into, but I thought I could also shed some light considering I was a CS major who worked in the DS field at a top tech company and am now in MM IB. Yeah, sure, data science is an interesting field, but a lot of buzzwords in the job descriptions depending on the role don’t do it justice. As a junior entry level data scientist, the constant coding, cleansing and fine tuning you spend 80% of your time doing gets boring. At least for me, expectations didn’t meet reality. Not to mention, over time the pay flattens out with no clear career moves upward except maybe to a PM position that everyone in both DS and SWE competes for. A majority of the time someone was given a fancy new title, with a small pay increase, and not really that much differentiation in the day to day work. To your point about entrepreneurship, I have a hard time seeing how being a data scientist prepares you any better to build a company as compared to IB. If you’re referring to the ability to code, although my background in computer science has given me some ability to write software, a large group of people I worked with did not have much experience with software development. There are individuals at the bank I work at with equally impressive quantitative skills that could’ve easily been data scientists as well. Having seen both sides, not to knock data science, but i personally prefer working in IB. Data science is definitely an interesting field some people thrive in, but hearing trolls on here with literally zero comparable experience hype it up as the holy grail and end all be all is frustrating. At the end of the day it’s just another job. Do the one that you enjoy more.
At your tech company, did senior DS focus on more novel research in ML? My classes were simply cleaning and understanding the theory behind a .predict() in python, but we didn’t touch the actual implementations and how those could be modified
I will try to speak generally, because as someone mentioned below, depending on the field you work in you could be doing a variety of different things. Yes, more senior members on my team specifically dealt with generating proposals for new internal and external projects as well as reading up on current research and techniques. But, it also really depends on your skillset and role within the team. Although most senior staff all had similar tasks such as reviewing code & models, feature generation & model exp., building deliverables & translating findings, and basic admin work, it still varied. Some people favored the engineering side and could easily write advanced implementations, whereas others were more pure mathematicians and statistical wizards with PhDs
Data science is not Finance, let me be more accurate, it's surely part of it, but definitely not the same breed of people as someone going for a proper Finance career in terms of character.
I completely agree with you. But, just to clarify for people, the transition that I made is not a typical one by any means and was incredibly difficult even coming from a target school. And obviously the skill sets are completely different, but the people I know that could do both are naturally talented and smart people that could have done either but instead of going the data science route in college they chose to do IB internships sophomore and junior year and then full-time.
I study data science, did a data science internship, and considered going into the industry. I chose to recruit for finance/IB for several reasons:
Again this is just my perspective based on my experiences.
not trying to attack you, but how much do you actually know about data science?
To the uninitiated population such as the OP and certain commenters: do you even know what the fuck data scientists are? Are you talking about the data analysts from undergrad who spend most of the time doing regressions using simple coding and making PowerPoints, or the actual data scientists who usually require a PhD in STEM for entry.
Judging from the 40k salary, it is the former, and that unfortunately reveals the abysmal level of knowledge OP has on this topic. As a Math major who knows a few people from both sides, I can assure you that the data analysts that you mistakenly referred to as data scientists, require little to no skill or intelligence. The work they do is mundane and often pointless, and many of them are dumb as shit. If you'd like do a comparison with IBD, at the very least you can do a little bit of research on your own position.
Hope that helps
Seriously, I'm asking myself this question every day. I am a BB IB analyst, but actually with Math and CS degree. My CS major peers are earning more than I do, doing more interesting work, and working 40- hours a week. I'm thinking about switching to tech industry now. Not sure why I pursued banking out of college, but apparently it was a bad decision.
Is this really the case?
Yea. There's no purpose for me to lie tho. But I prob won't do software engineering cuz this is not something I'm passionate about either. Maybe product management ish work.
Because about 3% of people here have the capability / skills required to do ‘data science’ at the level that the other 97% associate with the phrase. For everyone else a data science job would basically be what they’re doing now except if all the time they spent learning PowerPoint had been in excel and vba
I work pretty closely with a Data Scientist. Mind-numbing work if you'd ask me. Half of his data analyses barely achieve anything for our department goals (and are often incorrect predictions based off on how out of touch upper management is at times).
because I dont like data science lol
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