Data science in finance reddit To learn data science for a finance career, I recommend enrolling in courses at TutorT Academy. Data science is increasingly being used in the finance industry for tasks such as risk management, fraud detection, algorithmic trading, and customer analytics. 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. Also data scientists in some companies who aren’t sure what goal they are hired to achieve. As u/Cunning_Plan says, there are countless fascinating uses for data science all across the financial services industry, from banking to insurance to investment funds and having the additional knowledge and authority of a professional qualification like CFA behind you will be a real bonus when getting interviews. sql, python, and maybe r will get you much farther than working in excel and asking others for data. And they get disillusioned. imho, the finance analyst will go away unless you are at an investment firm. 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). Graduating from a Finance/Econ PhD program soon, now based in NYC. The tech industry and data science has saturated in comparison to itself than it was 2 years ago. Top IB and quant jobs etc pay a shit ton. Yes, you can pursue a data science career in finance. Only within the last 3 years have I even worked with someone who held the title as data scientist. . You will need to study finance on your own and try to choose as many finance-related electives as you can but learning finance on your own is a hell of a lot easier than data science would be. This is super encouraging! I was actually thinking Quant Finance would be a better industry destination for me given my domain knowledge but also have been considering Tech given the rigorous stats/econometrics I've received and comparative advantage in causal inference. g. CFO), whereas Data Science would peak at something like a chief of insights/analytics for a company. data analyst and data science skills will likely be the future. Caught between data science and finance (trading). Dec 30, 2024 · I may be an outlier case, but never once have I had to learn R or Python to do my job. Personally for trading I prefer data science students over statistics. 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). Oct 16, 2012 · I currently work in data science/machine learning at a tech unicorn, so have tried both the tech data science and finance jobs. In many ways the jobs are more similar than I thought. Salary will be higher on the Data Science side for sure, especially starting out. While specific data science applications are almost never completely unique to a specific industry, different industries do tend to have a different combination of or focus on specific use cases, like the financial industry’s investment in natural language processing for customer sentiment applications or for gauging market confidence based on the There are far more candidates than there are jobs. May 4, 2022 · Working With Shorter Feedback Loops. 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. Data science on paper may not necessarily land you a $150k role magically but that’s only because not many companies know what data science is, or the fact that it’s exactly what they need. Need career advice and a better understanding of the data science side before I make a decision. Yes, an MS in Data Science. Your degree will only get you the interview. How does a data science career evolve over 5 years, 10 years and 30 years? Economics is very good as bachelor’s degree, but it is not enough on the master’s level for data science. Skill sets between data science and quant finance do overlap, but there are also differences, like C++ & stochastic calculus for certain areas in quant finance. Jan 5, 2025 · Also another good thing about the CS is that it is a science degree and heavily contains math, data and the use of algorithms, which these skills are transferable to almost any industry or job role, even in some finance roles, where as many of the concepts learned in finance are niche based and are not really transferable. 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. Though I can see Finance leading to very senior and executive positions in a company (e. What are the best applications of Data Science in Finance? Particularly in Investment Banks, Trading, and Investing in the markets in general. Recently I came across this post on data science in finance. Of course, we all want to keep growing and improving, so I just keep doing so and from time to time trying to get more involved into Data Science, so hopefully one day I can make another post of "non-STEM background transitioned to Data Science". High Finance pays a lot yet. Or their work never makes it to production because of some reason or another. 2) the hours. My guess is that it is easier to start in quant finance and pivot into data science than the other way around. Then what are some limitations? I've read a comment by a Data Scientist that, predicting stock prices through Data Science / Machine learning is a "pie in a sky problem" and hence is not realistic. And if you think the top fin jobs would be easier to get, you are quite mistaken. The knowledge and capability you bring into any role is what will set you up for success in more lucrative roles either laterally or externally. Or they don’t even have the right data to work on. In both my quant group and DS group, I collect data, build models using statistics and machine learning, and write production software. But so do top data science roles in big tech. bagv gboe sdoy hindif ezprbi pcoq obcdq wtpq qqrpk nswlfy evjm trr kirwye ibay otnmf