High School College Application Advice

I'm a junior in high school, and parents, teachers, and -- perhaps most pressingly -- scholarship/summer program applications are asking me what college I want to go to and what degree/career I want to pursue.

I'm interested in financial careers, but my primary interest right now is software and data science. I've been told that quantitative finance would be a good career along these lines, but that most good jobs go to masters and PhDs. Some options seem to be:

1) Majoring in either math or CS with a minor in the other one

2) Double majoring in math+CS

3) Going for a 4-year master's in either math or CS

Are these actually logical or am I just being an idiot? Is it generally better to work before getting a PhD? Is a PhD even particularly useful? All else being equal, I think I want

1) A high-paying salary over the course of my life

2) A job that is actually intellectually stimulating with regard to data science

3) To go to school for the minimum length of time

Then again, I'm a stupid 17-year-old and maybe that's not the right order of priorities for the long term.

Does this type of plan change which schools are targets? According to this site, targets are UPenn, NYU, Harvard, Cambridge, Cornell, UT Austin, Columbia, Duke, U Chic, and U Mich. Does this list stay the same? Is there a strong ranking even within these? Does going to Cambridge severely limit opportunities to work in the U.S. after graduation (I know that there are many opportunities there for a 4-year master's there)?

How do quant salaries (for bachelor's, master's, and PhDs) compare with those of someone who goes into IB immediately after undergrad?

I've also been told that in finance more emphasis is placed on things like GPA and SAT scores than in tech, even to the point where I've been advised to retake my 1570 SAT score. Is this stuff true? Do employers really ask graduates for the SAT score they got in high school?

tl;dr As of now, when people ask where I want to go to school and what I want to study and what I want to do I say "I can't really tell colleges apart and I want to study either math or CS and I want to do data science or some kind of quantitative finance." I need help narrowing this stuff down and am not remotely well-informed.

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Comments (23)

Dec 28, 2018

Few things, personally if you can wing it, id do the double major in Math + CS.
If your SAT is 1570/1600, you're set. If it's 1570/2400 you've got a long way to go.
GPA and SAT definitely are weighted significantly. BB banks like UBS and Credit Suisse did ask for my SAT scores. It varies company to company.
Being a quant should net you a solid salary.
Cambridge is an excellent school BUT keep in mind if you want a job upon graduation in the US, the easiest way I can imagine is on campus recruiting at the target schools you mentioned. Just know that not all target schools are equal. If you go to Princeton, and Major in Sociology with a 3.0 GPA, you've got a better shot at any of these jobs than a 3.8 Math kid from UT Austin. School matters, Harvard/Penn/Princeton and such are definitely the way to go if you get in.
Find a few job positions and companies that you'd like to work. Then research which schools they go to for on-campus recruiting. That can be a definite list for your target schools.

thots and prayers

Dec 28, 2018

It's 1570 out of 1600 lol

Double majoring sounds like a good plan, though it would prevent me from chasing a four year master's degree or anything like that.

And I think some schools, like Princeton, don't have double majors.

Are the top salary jobs most going to PhDs or is there an opportunity to break past that initial line of defense with just a bachelor's or master's degree?

Also, in another thread like this I read about something called an MFE, and that these are often regarded as being equal in value to a PhD in a hard science/math. Is this true?

On a side note, I'm still finding it difficult to rank in my mind the very top schools, Harvard/Penn/Princeton/etc.

Dec 28, 2018

1570/1600 is super solid. Congrats on that.
If you have to choose one just go for CS....
Although you probably can't go wrong either way, as they both count as quantitative majors.
See thing is, if you major in Math, yet can prove that you've got a bunch of programming languages mastered, no ones going to care about your major.
As for the ranking, here's a story.
I was at an IBD recruiting event @ a BB IB, and a bunch of us were talking to the Group Head. I go to a somewhat semi-target school, and a few other kids with me went to UVa. We were all Finance majors. I kid you not, this black chick comes up (not racist, she was quite a character), she went to Harvard for some freakin music degree, had the most bizarre questions, she basically had zero clue about IBD, and pretty much the Group Head turned the discussion into a one on one chat with her (Even though all of us were standing there, trying to ask a question that would've impressed him). It was BS cause she was asking batshit questions. Said Group Head gave a long speech on how they don't even care about the major, they just want good students.

I think Harvard, Princeton, Yale, Columbia, and Penn-Wharton have their own rank among elite schools. If you're at Harvard majoring in bullshit, you probably have a better chance than some Cornell Finance kid. I'm speaking from my own observations here, maybe it's the other way around.

Basically let me put it this way
You go to Harvard/Princeton --> Major in bullshit--> Complete HBX CORe ---> Get your dream IB job
If you go to an BB IB recruiting sessions, they'll tell you they frankly "don't care" about your major, that's because they know Columbia and Harvard don't have Finance as an undergrad major.

If by MFE you're referring to Masters in Financial Engineering, then that's a solid program to go after. A bunch of guys at said BB IB event mentioned above actually had MFEs.

Just know that I'm speaking from my own observations and experiences, obviously someone who's a certified user is going to have more accurate advice. I'd suggest you do your research, and connect with Alumni of your targeted programs, and hear what they have to say.

thots and prayers

Dec 29, 2018

Wait until your college acceptances roll in before deciding what salary you deserve.

    • 1
Dec 28, 2018

I don't see the point of your comment. Could you point to where I'm deciding what salary I think I deserve?

    • 1
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Dec 30, 2018

College applications are a dice roll. No test score or GPA assures you admission into a top school. Focus on high school for the moment. Reevaluate your situation when the cards are dealt.

Also, don't underestimate the important schools place on extracurriculars. Top colleges want well-rounded students who will contribute to a more diverse student body, not just someone who can do well on a test.

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Dec 30, 2018

If you're interested in CS, I highly recommend you to take up competitive programming while you still have time. There are three more USACO contests this year (in January, February, and March) - try to promote to the Gold or Platinum division by then.

Visit Codeforces.com frequently to improve your CP skills: it combines math, CS, and encourages algorithmic thinking in general.

Dec 28, 2018

I made it to Silver on the last contest but could only solve one of the Silver problems. Bronze is basically ad hoc so I still have a ways to go.

CodeForces plus theoretical study through CLRS should probably get me to gold and possibly/hopefully get me to platinum by the March contest, though getting to camp is probably out of the question.

Other than that, I have some apps on the Google Play store and am thinking about marketing/monetizing/expanding. I've made and app for the local badminton club to run their tournament pairings automatically and I've got one other business (hopefully a few more, but the hunting is extremely tedious) that'll let me make them a real website. I enter research competitions in the CS division but my results are middling at best.

I think I can build a very strong application, but at the end there's always a degree of luck for those of us that aren't Olympiad medalists or literal scientists.

Dec 30, 2018

Just to add: Princeton and MIT offer Master in Finance, and UCB/CMU/UCLA/Columbia etc. offer Master in Financial Engineering.

Dec 30, 2018

go to the best school that gives you a full ride - do mfe at top program if you need to - profit

excel is my canvas, and data is my paint - new york - brunch conesseiour - atheist - centrist - ENFP - TCU alum

Dec 31, 2018

if you have the aptitude/ability to major in Math....then major in Math. Advanced Math is the rarest skill....and is the most highly sought after.

Computer science is a relative waste of time when it comes to finance. You can learn the necessities of computer science from free youtube and coursera videos.

When finance firms look at computer science skills, all they really care about is your ability to
a-database
b-solve logic problems and implement the solution by writing code

But both of these things can be learned outside of college for free...so wasting your college tuition on them is, a waste.

a-database is just a storage container of data....you create the storage container with the format best conducive to store and retrieve the type of data you will be working with. This just means figuring out what tables and columns you need. Easy right? Then you setup inserting data, and retrieving data to/from those tables. Its not rocket science.

b-solving logic problems by writing code. This is a 2-step process
1-learn a programming language. any modern language will suffice, but since you are interested in data science, choose Python. Its easy to learn, and was purpose built to support data science. Learning the basics of a programming language is surprisingly easy. Here is a 4hour youtube video that will get you a top to bottom introduction.

2 - After watching that video, the next step is to learn HOW to use those basic programming skills to solve problems. There are a few books on algorithims that you should read, and then attempt to implement the solutions on you own. Learning how to program is actually a repetitive process of writing code to solve simple problems, and then progressively solving more complex problems. Every step in writing code is simple....its just being able to juggle all the steps in your head, so that you know "what should i do next" that makes somebody a good programmer....and the only way to get there is a combo of practice with trial and error. Programming is similar to a physical sport, in the regard that you learn by doing. You can read all the books about playing tennis....but that won't make you a great tennis player...only practice playing tennis will improve your tennis skills. Its the same with writing code...only trying to solve a problem with writing code will make you good at writing code. You start with a problem to solve, then you research what are the best ways to solve the problem (you might start by searching stackexchange.com)....then you write the code to solve the problem...and then you go back and try to make your code better (fix bugs, make certain processes more efficient, maybe you'll think of a better way of solving the problem...better being more elegant, more efficient, handles more possible situations, better understanding of edge conditions, etc..). Since you only really learn how to code by practice, it would be a waste of time and $$ to major in computer science when all the teaching material is available in free online courses...and the Python is available for free.

Math is a more difficult nut to crack. If you are not a math savant, then you will need lots of hand holding and guidance from your math professors, when it comes to the more advanced topics. The advanced math is where the big $$ is (in this quant developer career path), because so few have those skills. Basic law of supply and demand.

However, if you want to build apps, maybe build a startup company based on some tech design....build the next AirBnB, then computer science (double major with marketing) is the major for you. But, if you want to be a quant, then just major in math, and learn how to program on the side.

This brings me back to your original question with a question....what do you really want to do with your life?

just google it...you're welcome

    • 1
Dec 28, 2018

I think you forgot to link the Python video, but it doesn't matter. I'm proficient with Python, and I have some (not not a lot of) experience with SQL and other databases.

I agree that the math is harder than the programming. A CS degree has the advantage of being transferable to a career in data science/AI as well, though. Is machine learning and the like widely used in quant research, or not really?

Dec 31, 2018

machine learning is used by some, but not all quants. Most all quant research will require you to understand how to construct a non-linear curve to best fit some kind of non-linear data (understand how the math models work, and be able to manipulate them....and there are multiple ways to do this) as well as other non-linear math models...this is not necessarily machine learning (tho machine learning will do some of these things also).

Its relatively easy to setup a tensor flow neural net in Python...but depending on the initial problem set, a neural net is not always the best solution. A good quant understands the problem, and also understands the minutia of what the different types of solutions can offer, and then chooses to implement the best solution for the given problem. In this way, being a quant is a bit more art than science (since we are always working with some degree of unknown). The only way to understand the minutia of how different solutions will affect a problem set is by understanding the more advanced math...which is why i strongly suggest majoring in math, if you have the aptitude. Learning the coding aspect (to the point where you can implement any solution with grace) just takes practice...but the same can't be said for the advanced math.

Both Math and computer science are transferable skills....math moreso in the finance world...computer science in a variety of tech fields.

just google it...you're welcome