And at top houses one would be competing with some of the brightest math students in the nation.
There’s a reason those companies are sponsoring math competitions as early as middle school…
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Yes, there are definitely other opportunities at financial or consulting firms for econ majors. However, finance is a much more common major than econ. A CS or data science minor certainly helps - for example, for a trading role.
The firms I have worked at, and others I am familiar with, do not have a special preference for athletes.
No, that’s rare. Most students only get an internship opportunity after their sophomore year.
Yes, most of the big-name firms do this, and many of the smaller or regional firms have started doing this as well.
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“fintech” typically refers to jobs where technology is directly used to facilitate a business function or solve a business problem. Functions like trading, portfolio management, research, sales, distribution, trade processing, back office, etc. There is also infrastructure technology - providing the hardware, networks, phones, etc. which is also critical to keeping a firm running, but isn’t specific to finance and hence not “fintech”.
Schedules revolve around market hours and so aren’t really flexible. Hours vary based on which part of the firm you are working with. Those working with a trading desk usually start an hour or more before the markets open; those working in middle and back office functions often have to work late into the evening because of the nature of their work. On the other hand, those working with sales and marketing teams for example, may get to keep better hours.
Stress level varies significantly - again, based on what your role is. Working on a trading desk, for example, can be very stressful. There’s a lot happening very quickly, and if problems pop up, they need to be resolved very quickly because there’s money (literally) being lost every minute. Generally speaking, “sell side” (broker-dealer/prop trading/investment bank/etc) fintech jobs tend to be much more intense and stressful than “buy side” (fund managers/insurance companies/etc) fintech jobs.
Wall Street was traditionally not a remote working environment, but the pandemic changed all that. Pretty much everyone switched to a fully remote environment, and have now (post-pandemic) adopted a hybrid working policy, where employees work some days of the week in the office and can work remotely on other days. So it’s definitely much more of a remote working environment now than it was previously (which also provides for a better work-life balance). However, I know of no financial firm that’s fully remote, and some fintech roles do require in-office presence.
Most entry level fintech jobs start with a 6-figure base salary plus a bonus. The exact base varies based on location and role. From then on, compensation varies based on your role (and can increase quickly and substantially) and whether your bonus is tied to your business unit’s performance. As you progress in your career, bonuses become an increasingly larger portion of the total compensation.
@DadOfJerseyGirl I’d be very interested in your perspective on how disruptive technologies like ChatGPT could/would affect your business, and perhaps even more broadly, the whole financial services sector, particularly in relationship to technology spending and hiring.
Hello @1NJParent, thanks for the question. I’m sure this is on a lot of people’s minds.
We are always watching for, and evaluating, new and emerging technologies to understand their impact and the opportunities they present.
ChatGPT is getting a lot of buzz these days and we’re definitely studying it. Its biggest feature is its natural language capabilities, mainly its ability to generate human-like text. But it’s still “artificial” intelligence - in that, it produces answers drawing from a vast warehouse of data but it lacks originality and creativity. For now, it can probably help automate tasks like creating boiler-plate text in marketing or legal documents, writing basic well-known code blocks, and so on. What it cannot do is, for example, write new original software solving problems that haven’t been solved hundreds of times before.
Bottom line: these are early days and we’ll have to see how the product and its competitors evolve. At least in the short term, I see it helping (making processes more efficient) rather than hurting (taking away jobs).
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Can you discuss the criteria a quant firm uses to choose candidates with math and computer skills for internships and entry-level positions? Also, how significant is the prestige of the candidate’s college in the selection process?
Aside from the technical skills needed for the job, firms look for genuine passion, analytical ability, and creativity. For those who “get” math - and can apply their deep knowledge to solve complex problems, not simply those who have taken the right classes. So candidates will be tested on how they think, especially when confronted with unusual problems or seemingly unsolvable questions. Can they think outside the box? Can they explore alternate solutions when they go down a particular line of thinking and get stuck? How do they solve a non-math-based logic puzzle? etc.
So, some firms are still prestige driven in this area because the quant desks are closely aligned with the rest of the firm, and many of the big-name firms are prestige driven in hiring. But this has changed/started changing at many firms.
Even when not prestige driven, the quality and rigor of a school’s program are very important (and this doesn’t apply just to quant hiring, but most of fintech too). Sometimes it’s hard to separate quality from prestige. For example, many firms will hire quants from Princeton because they have a very strong math department and have some of the brightest minds in the field. So it makes sense to shop there for quant candidates, and some may say it’s because of Princeton’s name but it is actually because of their program.
The same applies to other areas of fintech - reputation and track record matter. Many of the schools that show up in “top 20 CS schools” lists do very well, and you’ll see a lot of these are public flagships.
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I think it might be useful to describe the different types of financial companies that look for math and computer science skills (I was thinking of fundamental investment shops vs quant investment shops vs quant trading firms). And then within those companies, the major roles within them and the skills most important for each role.
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I’m somewhat skeptical that many extremely strong math students would end up with “no coding” abilities or would need to do something like a masters in CS to learn them. I ended up doing a lot of mathematical modeling after my math PhD but the coding was entirely self taught, I never had a single formal course in CS. Back then it was Pascal, Fortran, COBOL, Visual Basic, SQL, etc and all of these were easy to pick up on the job (though Excel is more important than any of them), nowadays it would be R and Python. My closest friend as an undergrad in college (who ended up as head of derivatives for a famous Wall St firm and wrote a well known textbook on derivatives) was the same.
For firms with sufficient resources, they tended to separate the jobs for those who create models and those who implement models. PhDs in math or physics can undoubtedly implement their own models, but probably not most efficiently (in terms of execution efficiency, portability of codes, and/or the use of their times). This isn’t universally true, however.
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Thanks for the suggestion. However, I think a complete answer will be too complex and too long for this thread. There are many different types of financial companies: investment firms, prop trading houses, wealth management, insurance, retail banks, investment banks, crypto trading firms, broker-dealers, retail brokerage houses, exchanges, custodians, and many others.
Then if we look at any one of these: for example, a money manager that offers mutual funds and ETFs, there will be many different kinds of tech teams within the firm. Teams that work on portfolio construction tools, trading platforms, trade processing and back office systems, systems that support sales, marketing and distribution, a team that builds and supports a retail or institutional client portal, etc. Some teams build in-house systems from the ground up, while other integrate 3rd party applications with their own.
The CS skills required by each of these teams vary quite a bit, hence my point about it being too much to list here across all types of teams and financial firms. As for the math skills, that’s not my area of expertise so I can’t provide guidance.
I didn’t say “many”. Way back when, there were certainly some who either, didn’t have sufficient coding skills or didn’t want to do it, preferring to focus on the models and analysis. As @1NJParent mentioned, some firms used to have a tag team that did most of the coding.
As I mentioned above, this isn’t the case any more.
I don’t think anyone on this thread said that. I’ll also note that master’s programs are not designed to teach coding skills.
Thank you for your dedication to supporting the CC community. Could you please provide guidance on how a student majoring in Computer Science and Mathematics can effectively prepare for a future career in finance during their college years, including recommendations for course selection, club involvement, research opportunities, and building connections with industry professionals?
Top firms recruit heavily among the math and CS competitions crowd.
And the crowd that gets involved with these competitions typically has a history of doing it going back to middle school - not because they want a career in finance, but because they love this stuff.
Incidentally, this is exactly what these firms are looking for. That’s why the sponsors lists of the likes of HMMT look like a Who’s Who of quant trading.
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I work at a quant firm. All our PMs/quantitative research analysts have an MFE. That may not be necessary at all places, but perhaps in smaller/mid-sized shops, where I work, it is a requirement. Something that is truly necessary, particularly if you work in smaller shops, is the ability to communicate. There will be onsite prospect meetings and client onsite due diligence visits. Being able to communicate the investment process or alpha factor research projects or participating in client service calls can really distinguish yourself from the pack. Again, I am at a smaller firm, which has allowed me to learn so much more than being siloed (such as running a firm, not just PM/research), and we have a couple of analysts that will never make it to PM because of their lack of client facing skills/ability.
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For students interested in a career in financial tech, is a CS degree preferred over a degree like Operations Research/Financial Engineering or Operations Research/Information Engineering?
I guess it depends on what type of work you are looking for. None of our investment team members have an undergrad in CS. They have Math, Math/Econ or engineering degrees. Most have Master’s degrees and have an MFE (so 2 masters). Operations research is also desirable. We have PhD’s as well. 99% have CFA designations.
Our CS degree members are in IT implementing the code. In our early days as a firm, we had MFEs doing the coding (we were a start up). Then when we were able to hire CS people, I’ll remember the guys telling me how the code wasn’t “elegant” and we had to revamp a lot of the code. So for a firm like ours, having CS for implementation is better.
Here, for example, is an overview of various roles at Jane Street:
and in more detail:
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