Data science to quant reddit salary.

Data science to quant reddit salary Quant Analyst in Model Val, 14 years experience mixed between QD, QA, in FO-adjacent role. I. Our goal is to help navigate and share challenges of the industry and strategies to be successful . 151 votes, 138 comments. 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. Really good to have this perspective when someone tells you their salary. Because most Data Science jobs are Data Analyst jobs There are a few reasons for that: 1. Econometrics you will have a deep understanding of one the most widely used methods in statistics, data science, quant finance and programs like EME require you to learn those tools using more math than most American engineering students take. Of course DS is another story but there is definitely a relation between political science, sociology etc. Like 6 months professional + couple months internship. ~£175k salary (after increase), last year 30% bonus (before increase) but not looking so hot this year. For data science emphasize stats and ml knowledge over coding. I currently work as a data engineer for a quant team, my official title is quant data engineer. Your degree will only get you the interview. There aren't a lot of quant firms or banks hiring quants compared to all the big tech companies and tech startups. The biggest advice I can give anyone trying to break into the industry is "practice, practice, and grind". I broke into the role by actively pursing openings and interviewing via recruiters. Quant research is probably the toughest to get into because there are only a small number of positions and the pay is much better. My 2 cents: given the raise of AI go for some applied statistics like data science. However, now with widespread hiring freezes and layoffs across big tech, is actuarial now a relatively better value proposition? As a quant with around 14yoe, I tend to agree and disagree with the some of the comments here. Company/Industry: Public company with an R&D focus. A space for data science professionals to engage in discussions and debates on the subject of data science. Although I am not that familiar with risk roles, I have heard they pay less than other quants especially those generating direct alpha. $200,000 in the Valley is a very normal Data Scientist salary when you adjust for how much companies have to pay the average employee in the region. Salary: $265k. Often they can benefit from top data science. Fortune 150. Based on the dataset, a career path in data science, particularly in a senior or managerial role within the finance or tech industry, and located in a major financial hub like London, would likely offer some of the highest salaries. 25-40 hrs a week (2-4 days in office), flexible re: family Generally happy, will have better opportunities if I can stabilise family situation. During my masters, I got a data science internship at a (~1,000 person) tech company. For example, risk management Quants collect data on market prices and positions, analyse those to forecast likely future returns, and make recommendations such that certain trades should be reduced or hedged. I am aware of PMs getting paid +$50M in the most successful teams Quant Developers: $300k - 1M Over the past few years, comps have increased substantially due to the increased market volatility. ) Thats a common tactic for companies to get more skilled people into their companies because these people are more interested in Data Science compared to Data Analytics ("Data Science is the sexiest job of this century") 2. It was a data set I actually received as a technical interview of synthetic salary data and made a salary predictor based on 6 factors. true. Make sure you have some coding knowledge in R or python and SQL. 39 votes, 14 comments. From what I have read I truly do believe actuaries are underpaid. A subreddit for the quantitative finance: discussions, resources and research. It’s 100% more academic. I’m an international student and had 0 offers up until March. Data Science is probably less time consuming, but a harder career path. Actually, it is quite common to work in data analysis with a social science degree if you had a focus on stats and quant methods. The role was sold as a data science manager, yet ended up doing admin work and touched on very small amounts of actual data science projects. My guess is that it is easier to start in quant finance and pivot into data science than the other way around. Adding a few other data sources for UX salaries: User Interviews UXR Salaries (2020) - scroll down for a chart by years of experience UXPA UX Salary Survey (2022) - mostly researchers and designers, see slide 17 for data by years of experience. How did that help me get interviews? I work in London fyi. The base salary is usually 150 to 200 (more in IB). CSCareerQuestions is a community for those who are in the process of entering or are already part of the computer science field. 5 years. b) I think it depends on which area you want to work on. #1 is my very first option and what I would like to do and #2 is more so of a backup. Data Scientist Masters of Science 5 yrs $108,000 per year $16,000 bonus Coppell, TX Considering my current options, looking… Citadel made 28B gross last year, and returned investors 16B net of fees. But the culture is not for everyone. The explicit barriers to entry are highest for actuaries because of the exams but I think quant research and data science attract better students. Typically high salary jobs in the data space will have some barrier to entry, whether it be MS/PhD, as well as domain knowledge, experience which may time-gate you or potentially prevent you from getting your foot in the door. a) There are several good services nowdays which gives you infrastructure with data/historical data and API for order execution. $300k+ starting salary if you're a PhD grad from one of the top research groups in the world, and land a gig at DeepMind, FAANG, etc etc etc. • Title: Data Scientist • Tenure length: 2 months in current role, 2. Sep 4, 2020 · There is clearly a huge overlap here between a data scientist and many Quant roles. 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. I am a data analyst that previously wanted to be an actuary. It's likely more similar to a tech data science role in that they are helping discretionary portfolio managers make investment decisions. But there's so few jobs, where they pay you so little, and who knows if you even have a voice in these organizations. It was great! Quant Researcher/Trader: $400k - $5M Quant PM: $1M - $20M. (and also data science at FAANG, although that's less relevant), and I was and I don't know if this is true but it seems like tech jobs that have similar skillset as quant such as programming/data science and have similar pay are also less competitive to break in as well. The average remuneration package is still huge regardless of the bonus, and when asking about a particular job most people assume a base comparison to the general population. My salary is about the same as the quant developers (a little less but not much) I spend my time creating data pipelines for alternative data sources to improve forecasts, creating data warehouses for analysis, cloud security and architecture. There probably big difference between actively trading hedge funds, and slow investment funds which rebalance portfolio once in a while. $200k is not a low salary in terms of what you can buy with it, as most people think of a salary relative to the lifestyle it provides them (e. Data analytics in HR or some like to call it People analytics is similar to any other sort of data science out there just we focus more on optimising workforce management. 6 months ago, it looked like data science and SWE was the place to be. As well, you're usually limited to Tech, Quant firms / Big Banks, or very niche companies in HCOL areas. 5 years in industry • Location: fully remote, located in the inland northwest US, company headquartered in Texas • Salary: $125k • Company/Industry: Property/Casualty Insurance • Education: PhD Physics • Prior Experience: PhD, 2 years as data scientist in same Personally for trading I prefer data science students over statistics. How is this I think the UK is attractive for quant research jobs, those have a competitive salary compared to the US. Also has historic data, which is nice! Small companies, with low headcount, need data science. g. com Jan 27, 2019 · There was not a significant difference between compensation for quants and devs, at least first year. Your math/stats skills matter much more than your communication and software engineering skills (assuming there’s are quant developers at the firm to implement strategies for you). I dont know of a lot of bachelors degrees that dig deep into machine learning and data science except for maybe 1 or 2 advanced classes. Both the Two Sigma and Citadel positions were quant dev. Here’s a quick rundown of their roles and typical compensation structures. See full list on resources. May 2, 2006 · After sharing the compensation data, I received many inquiries on LinkedIn about the differences in compensation among Quant Traders (QT), Quant Developers (QD), and Quant Researchers (QR). If you don’t have a technical background, years of experience as a data analyst, or are attending a top school, you probably won’t get a data science job straight out of school. CFO), whereas Data Science would peak at something like a chief of insights/analytics for a company. Members Online I Will Fucking Piledrive You If You Mention AI Again Tbh I would rather hire an analyst or have an analysts department, and train them up to do data science work so some of them can move into data science, than to create a junior data scientist position. Salary will be higher on the Data Science side for sure, especially starting out. Cost of living there is insane, and quant is a job in itself that should have salaries on the right side of the curve. Preference: Math, Statistics, Operational research, computer science, (edge profile) Engineering Capital Quant A capital quant works on modelling the bank’s credit exposures and capital requirements. That’s actually how I started, as an analyst on an analyst team, before moving to data science at the same company after 1. Books like An Introduction to Statistical Learning and Hands-on ML (part 1) are great resources for this. I have been working as quant researcher for about 3 years at one of the top 20 hedge funds in US (not quant hedge fund). Systematically banks are generally considered banks above 750 billion assets under management and are subject to highest standards for regulatory stress testing exercise and generally have The whole idea that quant is the most intellectually stimulating role in the world, is also bogus, from the standpoint that I’ve also talked to real data scientists, (who this subreddit likes to clown repeatedly), where their work is actually data science, and they do more modeling than some of the quants I’ve talked to. Full timers don't work for them because they are low headcount businesses. and data-driven work. As for normal data science jobs I honestly wouldn't know about the UK, but tears start rolling out my eyes when I see US salaries. if 200k bought you an apple then it would be a low salary imo). noodle. . Though I can see Finance leading to very senior and executive positions in a company (e. A minor in Computer Science or Business Analytics would complement the major well. Here is a bit about the companies: Company A: Role: Data scientist $10,000 signing bonus (repaid if leaving the company after 2 years) 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. I came back and decided I would switch to data science, but I was worried I would miss out on the clear, predictable, generous pay of an actuary. From the actuary salary progression threads it seemed about the same. Data science was still in its nascent stages and was more of a hybrid software engineering role at most places. Academia was and continues to be getting more competitive at every stage of the process: increasing hiring/tenure standards without the compensation to match. there's not enough reports and the level bucketing is suspect. I was upset about the role but my boss assured me there were “big things” in the pipeline. 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). For risk roles for major banks, there is a tiering based on asset size that effects pay and career. $45/hr No prior internships but 1 school research and an IT desk job Sophomore (rising Junior) Company in Midwest. You can be a middling actuary and make 150-200k when you are an FSA. In the accounting reddit if you make less than 6 figures after 5 YOE you are underpaid. The software engineering is incredibly easy compared to the real value brought by building data products and getting an edge on the market through data science. 20% of Citadel's investors are employees, possibly more (and the amount invested in the fund grows disproportionately with seniority/role), so in total citadel staff and board made 12B fees + 20% of 16B ≈ 15B. Nov 4, 2024 · You can go study real analysis, abstract algebra and measure theory. My initial interest in switching to a data analyst/data science/data career sort of revolved around sports analytics. I also teach two classes a year in the city for another $27k. Also known as a front office quantitative analyst, sell-side quantitative analyst, or quantitative pricing analyst Found in investment banks Requires an MSc, but PhDs are preferable Annual Total Compensation: $250,000+ Medium Stability Medium-Poor WLB High Stress High Prestige High competition and low demand Title: Engineering Manager, Data Science Tenure length: < 1 year Location: HCOL, Northeast Remote: Hybrid, in the office 2 days a week Salary: $227,000 base Company/Industry: Healthcare Education: STEM PhD (Chemistry) Prior Experience: 1 year in Data Science, 3 years in DS-relevant postdoc Internship: NA Coop: NA A space for data science professionals to engage in discussions and debates on the subject of data science. e you were top of your class in Stanford/Oxbridge/MIT etc and you did your PhD on some of the most revolutionary work possible. the data quality is not very good for those companies. 1. for example, L3 engineer makes less than L1 at jane street? I don't work there, but I've heard they don't have the concept of "levels" to begin with; it's whatever base salary you negotiate plus a large performance bonus. Whilst Data Science seems more statistics, python, SQL. If you are accepted into a restricted major under Science via direct admission (like data science, FST etc) then er I don't think you can apply for QF (not 100% sure about this) coz for restricted majors you cannot anyhow switch out of your major and to apply for another major you will need to drop your restricted major. So we do things like data collection for HR related items like demographics, pay, performance, employee engagement, recruitment, attrition, turnover, and training. 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 highest paying jobs for a MSDS are not necessarily broadly available. With an advanced degree you are looking at 5-6 more focused classes and likely research in a relevant area. Reply reply Captain_Doofus1 Working in quantitative finance, as a quant analyst, quant dev, quant researcher, or trader Working anywhere besides quant finance, as a data scientist. 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. Academia, social science research on longitudinal data (government funds) undergrad in psychology, certification in big data for social science focused in R + sql certification on datacamp which is totally useless in academia but i wanted extra skills to open up doors for later. FAANG was hiring like crazy with huge comp packages and actuarial pay was fairly stagnant. That is the standard in the US. That may change over time as data science degrees mature, but so far I haven't been impressed with those. Super uninspiring use case and data set. Dear Professionals and Elites I am an Econ & Math undergrad currently fall into hesitation of which future to choose: I received offers of master programs from NYU Data Science (expected but not sure for scholarship) and BU Mathematical Finance ($25,000 scholarship), expecting UCLA Financial Engineering to take me but not sure. I got a master's in Statistics (integrated program with bachelor's), and things have worked out great. That will be ur best bet. Not just monetarily, it means you can pick your projects. Members Online is it worth to take a data analyst course after flunking university? If you want to go data science, brush up on your stats and ml knowledge for interviews. Aside from the quant firms, I also had offers from tech companies. Yes, an MS in Data Science. I interned in quant research for a bit. The range of opportunities in this space is enormous. I call them the data scientist and analyst, before the term was coined, it is essentially portfolio optimization and inefficiency finder. Members Online • Abject-Bumblebee4881 . All these offers started a bit lower but climbed up after negotiations. Incredibly difficult I imagine. Yes, the interview process is especially brutal, since for some reason, you're basically required to be an expert in three disciplines (math, computer science, finance), and the positions tend be much sparser than say, a fundamental investment role on the sell side (as a strategist) or the buy side It’s been 6 months since starting a data science management role, and now have been laid off. I currently run the quant department at my firm and am constantly training hires from top graduate programs in ML and data science (as it relates to finance). Quant Research/Data Science Salary at hedge fund I am 27M with MFE from top US program - think Baruch, Columbia etc. Quant in a bank in London at 4y experience at 55k seems very very low. ) I do think getting a salary competitive with a fellow as a middling data scientist will be difficult. They are both giving me the same base salary but I am curious about what others think of the opportunities and potential career path (especially the Quantitative Analyst path/seniority levels). nxg tqxp jivofw dcw znjo zsbetb kqbys wjoxkh hpmo rvepyin vsdgaap yukln yxty upwipb cqyqtx