Data Science career path?
I'm enrolling back into college next year to major in Data science. I'm doing the community college to four year route and will hopefully obtain a BA or masters in DS. Will gaining work experience as a data scientist, from a non target school, be sufficient enough to break into a quant role at a lower tier firm? I live near NYC so i don't know how much a difference this makes. Im 25 at the moment so id graduate around 30/32. Any advice or insight will be appreciated thank you.
Based on the most helpful WSO content, here's what you need to know about transitioning from a Data Science background into a quant role:
Breaking into Quant from Data Science:
While a Data Science degree provides a strong foundation in statistics, machine learning, and programming, breaking into a quant role typically requires additional skills and experience. Quant roles, especially at hedge funds or trading firms, often demand expertise in advanced mathematics, financial modeling, and algorithmic trading. To bridge the gap:
Work Experience and Projects:
Coming from a non-target school, you'll need to stand out with relevant work experience and personal projects. Employers value:
Networking:
Living near NYC is a significant advantage. Many quant firms and hedge funds are based there, providing ample networking opportunities. Attend:
Age and Career Transition:
Graduating at 30-32 is not a dealbreaker. Many quants come from diverse backgrounds, including academia or other industries. What matters most is your ability to demonstrate technical expertise, problem-solving skills, and passion for the field.
Certifications and Further Education:
If you aim for a quant role, consider supplementing your degree with:
Targeting Lower-Tier Firms:
Lower-tier firms may have less stringent requirements compared to top-tier firms like Jane Street or Citadel. However, they still expect strong technical skills and a demonstrated interest in finance. Tailor your applications to highlight your data science expertise and its relevance to quantitative finance.
Actionable Steps:
With dedication and strategic planning, transitioning into a quant role from a Data Science background is achievable, even from a non-target school. Good luck!
Sources: Q&A: Quantitative Analyst - Machine Learning, Analytics, & Quantitative Research/Investing, New breed of Finance and Capital Markets Professionals, RE: Prop/Quant Trading - Why is it not as big a target as Investment Banking?, Advice On a Career, Q&A: Top Quant Firms First Year Comp 250k to 400k
As a quant or a data scientist? As a quant, almost definitely not. Data science degrees often lack the rigor required for quant. With a masters you could probably do data science at a financial firm, but you won't be close to the money.
It's really hard to understate just how tricky quant is, even at "Lower tier" firms. There really isn't too many "low tier" quant firms because the fixed costs of infrastructure are so high that you almost always have small but elite firms, or massive and elite firms.
If you do want to be a quant, you need a masters from a top school.
Thanks a lot for the insight. Just to be clear, are you saying obtaining a masters in DS from a top school will significantly increase my odds? Or, are you suggesting switching to a major that is more STEM focused i.e(statistics, Math, Engineering, CS etc) and getting a masters in one of these? Sorry if these are dumb questions lol
The only one I see somewhat regularly amongst quants is Harvard's MS in DS. You'd need a more traditional masters, like math, stats, physics, or CS. Some can do so with a T10 MFE(On quantnet list) and from there, you can probably land a buyside gig at a lower tier firm OR end up more realistically at a bank or financial firm.
just to add on to your solid points: masters in DS is okay for like alt data DS roles at HFs, but still needs to come from a decent school based on my experience and observations. getting a entry level gig in the alt data space has gotten a lot harder though in the past few years
Interesting, I work in macro/RV so we do some alt data, but most people coming in there have backgrounds in CS and AI/ML because the computer vision and parsing is something we see a lot of(a lot of sentiment about the broader economy for big models on the macro type stuff). I could see how a top masters in DS could work here, but it'd need to be a degree that was more about the hard skills over the traditional DS work that has been so common at tech firms in the 2010s.
ah interesting, makes sense. i would agree on your point about hard skills; my team at end of day is 100% cs, stats, math, or eeng degrees lol. but have seen alt data people with DS degrees at other firms, though they were hired like pre-2023 when firms were hiring data people like mad
When you say alt data people, do you mean alt data in a discretionary fund? Because yes I agree, systematic funds tend to have pretty high technical/prestige bars. Alt data is more accessible. You get very varied talent and opportunities (can be hard to see which seats are actually good). That being said, there are definitely some interesting opportunities for someone who wants to work with alt data but in a discretionary investing context.
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