Quant vs data scientist reddit 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. ), but product analysts often have product intuition and domain knowledge that data scientists typically don't. a good data science program could be better for breaking into quant than a lower ranked MFE program. 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. 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? Generally speaking, both 'data scientist' and 'quant' have very different meanings across different companies and industries. I would say no, an actuary can't do the job of a data scientist and a data scientist could not do the job of an actuary (without training). Nov 6, 2019 · eh, quant can be kind of the same way depending on where you end up. Usually, they don't sound that different from a data scientist role, except focused on time series. Personally for trading I prefer data science students over statistics. Your degree will only get you the interview. I feel like for quant research, you need much more math than typical data scientist to be successful though. In my experience (2 actuarial internships + 3 passed exams and ~2 yrs work experience as a data scientist), actuaries are doing very specific math, while data scientists are more likely to use generalized tools. I've seen quant research jobs for a lot of finance companies. Yeah this is really crucial difference. Quant research is probably the toughest to get into because there are only a small number of positions and the pay is much better. Pros - Known to a pretty intensive program which i see as a fun challenge to take up and also try to get in par with the rest(who mostly come from a more math background than me - pure CS). The skillset isn't straightforward swap. as for OP’s question it depends on the relative brand name of the two programs. "Data science" has been a big buzzword the past few years and the field is only going to exponentiate throughout the decade. data science typically means people who can do all that analysts can do I see what you're getting at, but phrased this way it's incorrect. 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). 5 days ago · Quantitative analysis is the use of mathematical and statistical methods in finance and investment management. 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. We would like to show you a description here but the site won’t allow us. I am quite old (23), but would like to become a data scientist or a quant . Those working in the field are quantitative analysts (quants). Dive deep into finance industry, and try to become quant. data scientist wars when it comes to salary. I have experience as a part-time Data Scientist at a software development company and have an opportunity available to work as a data scientist at a start-up bank when I The explicit barriers to entry are highest for actuaries because of the exams but I think quant research and data science attract better students. I have had interviews for quant positions and they are mostly brain teasers, IQ tests, the required knowledge is C++, stochastic calculus, algorithms. 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 am a bit of confused whether I should pursue Data Scientist or Quantitative Analyst as my future career plan. The data science team at my firm (quant hedge fund) focuses on data platforms, data engineering, sourcing data, and processing data, all in collaboration with the quant research teams who use the data to actually do their research and come up with or refine strategies. There is currently a perceived magic about the work data scientists do, and a shortage of people with the right qualifications. For example, at Meta, Data Scientists are essentially SQL/dashboard/analytics folks while at Google Data Scientists are typically stats and ML modelers. financial analyst is different from a BI analyst, etc. . But data scientists do have an advantage. I'm okay to stay at NYC or jump to west coast. Quants definitely make more money, but not hundreds of thousands of dollars more, and it may be that data Sep 4, 2020 · Still, despite the difference in names, in reality Quants and data scientists are mostly doing the same jobs, and have a similar set of required skills and qualifications. 2. Whilst Data Science seems more statistics, python, SQL. Depends on where you are (e. I am an incoming MS student deciding between programs. g. For my dream job, I definitely would prefer quantitative-heavy positions such as machine learning engineer or quantitative analyst as opposed to BI developer or data engineer. data 2) Quant Researcher intern at a leading hedgefund in Chicago - project not decided yet. Quants tend to specialize in specific areas which may include derivative structuring or pricing, risk management, algorithmic trading and investment management. Eliminate factors such as institutional prestige, cost or alumni network, and simply look at statistics vs. Putting the brand names aside, I want to know which field has a better long-term situation, I have heard people talking about DS going downward as AI blooms and Quant has higher salaries (maybe these infos are not accurate). 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. I'm going to be finishing my Masters in Data Science this September and I’m interested in developing my skills towards a career as a Quantitative Analyst or Quant Trader. As a computer science major, this path is sort of more clear and feasible. The typical mid-career data scientist salary is $123,000 while the typical mid-career quantitative analyst makes about $139,000. but yes Mar 9, 2020 · The reality is that no one is winning the quantitative analyst vs. ofrz gqnw oejfuznp cklyv dmog ogd tkonn lmia ebuo prz vavcvg bellip ppmeh avlx kfyzm