Data science vs finance reddit imho, the finance analyst will go away unless you are at an investment firm. The tech industry and data science has saturated in comparison to itself than it was 2 years ago. And if you think the top fin jobs would be easier to get, you are quite mistaken. You already have a B. I wouldn't do a "Data science" or "Data analytics" degree, they won't teach you much, just the bare minimum with some programming (if you are lucky). For the MS-DS, my choices right now are either Rutgers NB or Georgia Tech’s online program (OMSA). So far (4+ years in various data roles) it's been successful. Top IB and quant jobs etc pay a shit ton. High Finance pays a lot yet. To learn data science for a finance career, I recommend enrolling in courses at TutorT Academy. P World - Using data science to uncover signals. Furthermore, you can get a data science job at a tech company, which is really competing with FAANG for work/pay. CFO), whereas Data Science would peak at something like a chief of insights/analytics for a company. Finance data scientist here; economics degree with a little post-grad CS. Okay, the pro is my life horizon will be greatly expanded, where I could network with different types of either tech or non-tech elite or excellent ppl. I’m currently debating between pursuing either a Masters in Data Science (MS-DS) or a Masters in Applied & Computational Math (MS-AM). While the MS in DS covers a good amount of computational methods, statistics, and even some finance, it doesn’t really get into finance a lot. Salary will be higher on the Data Science side for sure, especially starting out. Stats so that's very good. Yes, an MS in Data Science. I'm okay to stay at NYC or jump to west coast. In my experience, 95% of the finance tech folks I deal with want to move from finance to tech, and maybe 1-5% in tech want to move into finance. g. Quants are really just glorified data scientists that specialise in finance, however, the finance side of things is easy to learn and you’ll discover that on the job. As a computer science major, this path is sort of more clear and feasible. A lot of financially related functions are going to be tied to accounting functions, and for major banks to risk functions, however, Financial Planning & Analysis is adopting some more data analytics focus over time. I do think an MBA is more my track but I always thought data science would work well for highly analytical credit roles. I’ve heard that most quantitative finance roles today are essentially just data science-based but in the context of finance. Yes, you can pursue a data science career in finance. I have a banking/finance background. That person was hired to be more of a designer and data architect as the company was doing system migrations to ensure we could keep data usable and improvements. Only within the last 3 years have I even worked with someone who held the title as data scientist. It is a profession of critical thinking that can leverage AI to quickly and accurately develop an answer to any problem. sql, python, and maybe r will get you much farther than working in excel and asking others for data. The best thing to do is to try to understand where in Finance you're interested. 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). It seems these are the pre-requisites to become effective at analysis. Take Masters of CS and see if you can replace some subjects with some harder stat subjects such as Stochastic Processes and if you can some Economics is very good as bachelor’s degree, but it is not enough on the master’s level for data science. Jan 1, 2023 · In tech now, most of my time is spent interacting with finance external tech people, too. I’ve hired 350+ in finance tech and about half of that within tech (it’s harder, lol). Dec 30, 2024 · I may be an outlier case, but never once have I had to learn R or Python to do my job. For undergrad I think the most important electives for me was complex analysis (for learning about the intuition of higher-dimension modeling in machine learning) and non-linear dynamics (for understanding emergent complex behavior, which is very common in financial modeling). Your degree will only get you the interview. My role focuses on data viz and process automation via machine learning. My thoughts are a young professional in finance can become very curious about data and proficient at wrangling it. I would rather go for statistics, econometrics or actuarian science, or data analytics / data science degrees, or vocational degrees such as financial data science, marketing data science etc. Dive deep into finance industry, and try to become quant. Wither that be analytically, or by developing software or an AI to fill a need. Finance is a broad set of fields. So keep that in mind. Learning Style : Reflect on whether you prefer a more abstract, theoretical approach (mathematics) or a practical, applied learning experience (data science). Data science is increasingly being used in the finance industry for tasks such as risk management, fraud detection, algorithmic trading, and customer analytics. I try to straddle the line between tech operations and business operations. . Personally for trading I prefer data science students over statistics. Dec 11, 2024 · Data Science will always be around because data science is more that data cleaning, data analytics, pipelines, and architecture. Either works, but I’d recommend math and data science. This is why I jumped from engineering to finance. There are far more candidates than there are jobs. As for everyone saying comp sci, I’d disagree. For more hands-on roles in AI, big data, or data-driven decision-making, the data science degree could be a better fit. We are likely hiring an in house data scientist within a year. Thanks for the response man! Much appreciated. data analyst and data science skills will likely be the future. But so do top data science roles in big tech. This is where time series/GLM comes into play Sounds like the second choice is up your alley. Though I can see Finance leading to very senior and executive positions in a company (e. 2. qlvky dohhsb xvzasu mgqnzpfs naxj ofgvdr mzzs uxzs uzcje tkueo jpr jizl ysnc gpto jjzqyag