Data science to quant reddit. So keep that in mind.

Data science to quant reddit I am seeking entry level roles. The you can easily apply that in quant fi or data Sci. , would help. I would say take numerical methods in python. The areas of Quant Finance that I am most interested in are Quant Trading and Risk Analysis. . A minor in Computer Science or Business Analytics would complement the major well. Feb 20, 2023 · I was hoping to get some insights about what steps I can take to break into Quantitative Finance as an MS Data Science student. So keep that in mind. Nov 6, 2019 · eh, quant can be kind of the same way depending on where you end up. I'm thinking about trying to switch from data science to quantitative research. Context about me: 33M, PhD in statistics (with a focus on theory) from a top tier school Since graduating, I've worked 2 years at a FAANG company doing data science. Is that really all the difference between the two? Is a quant researcher just a data scientist working with financial and time series data? If not, what exactly does a quant researcher do? As for the degree's level of prestige, if you will, involving masters programs and job applications, hardly anything will look better than data science. Why quant then? I don't think that quant jobs give too many opportunities for that. My 2c at least. Your degree will only get you the interview. Whilst Data Science seems more statistics, python, SQL. A space for data science professionals to engage in discussions and debates on the subject of data… I was originally working as a space systems engineer designing satellite systems. Business know how matters a lot, knowing some algorithms or technology stacks doesn’t make you a quant. Did real analysis undergrad for mathematicians and it's way too theory focused for a dummy like me. 8M subscribers in the datascience community. 1. Climb the SWE ladder, get very good at OS, Networking, and Algorithms, maybe pick up some C++ experience and some good names under your belts, then go into hedge funds / buyside quant firms as a quant dev. Current total comp is ~270k. Usually, they don't sound that different from a data scientist role, except focused on time series. Of course one shouldn't read it as "data science BAD" without any qualifiers, or that "data science-like quant" is bad. "Data science" has been a big buzzword the past few years and the field is only going to exponentiate throughout the decade. P World - Using data science to uncover signals. This is my first data science test so based on my studies and my hobby applications of machine learning, I found I could be competitive when answering the questions. Physics geek here, who's worked in data science. Current program: MS Data Science at Vanderbilt Jan 10, 2025 · Undergrad at Georgia State with sub 3. a good data science program could be better for breaking into quant than a lower ranked MFE program. Creating values with quantitative methods then you’re in I’ve always liked math and statistics especially and have been thinking about graduate school first, but long term I don’t think I won’t to go back to an industry data science job, but rather I want to break into quant research or trading. This is where time series/GLM comes into play Sounds like the second choice is up your alley. While I do like ML, I hate anything to do with images, videos or text data. Furthermore, you can get a data science job at a tech company, which is really competing with FAANG for work/pay. These classes taught me what statistics is really like, and showed me all the parts of data analysis I missed in my first four years of taking AI classes only here. I agree that some questions raised doubts about actual applications but overall I felt tested rather than overwhelmed which is why I gave my opinion as such. Program Options: Specialist in Statistical Science: Theory & Methods Unique courses: STA457H1 Time Series Analysis; STA492H1 Seminar in Statistical Science; STA305H1 Design and Analysis of Experiments; STA303H1 Data Analysis II; STA365H1 Applied Bayes Stat I've seen quant research jobs for a lot of finance companies. as for OP’s question it depends on the relative brand name of the two programs. Personally for trading I prefer data science students over statistics. but yes Mar 21, 2025 · Industry: Machine Learning Engineering (or relevant research roles), quantitative finance. This is reminiscent of many quant roles selling themselves as something fancy mathy while in the end being very similar to a data science role. For quant development, MS CS in tier-1 schools with great scores in competitive coding programs, participation/trophies from ACM ICPC type tournaments, etc. MS in Data Science will not get you into almost any quant trading/developer roles unless it's a startup prop firm or below tier-2. Being a quant regardless of field, alpha, risk, hedge, portfolio optimization is the ability to formulate a business problem and solving it in a quantitative data centric manner. At the end of the day the only thing that matters is how much you know and how well you interview, if you get past the initial resume screen, an MS in data science is viewed as a stat + CS guy and their interview questions will revolve around those topics (more so in ML). The work is somewhat research oriented. I have also realized that without any kind of domain knowledge, I am absolutely useless as a data scientist. Lower than F/G? Maybe, but I'd want to see the numbers to be truly convinced. For a career in quant or data science, a major in either Finance or Economics (with a focus on data analysis or mathematical economics) would be beneficial. I had to move into data science due to financial reasons. I would be pretty surprised if that were true. You're probably better off doing investment banking, sales, trading, etc. I was wondering if the skills are transferable and what people's thoughts are on the better career path? My current plan is do a data science bootcamp (I know they are a rip off), and am applying for quantitative finance masters for the following year. Below are some details about my background. 0 GPA means quant trading is pretty much impossible to recruit for. quant is a lot more specialized so u can get pigeonholed and if ur specialization is no longer a hot sub field, then ur kind of SOL. it seems the average pay of quant is worse than SDE. 200 covers inference which is essential for any quant/data science work, you will need to know things like p-values and hypothesis testing and apply inference into case studies, 75% Sounds like the author might not have realized this upfront. vmgu zjlc omxx nic toel ceecl eeysq eknabb fvk mep tygri fhxidv yhgj imydk qjib