Mle vs quant reddit.

Mle vs quant reddit That's just to get your resume looked at. I’ve had good wlb, reasonable comp, not too stressful. Startups looking for MLEs may skew more towards take home assignments, which may range from 2 hours (fine) to 8+ (not so great). academic research != quant research and there are very few things that overlap. do these job titles matter? Not really. I do not have a graduate degree (just a BS). i don't Heya, native speaker of MLE here (grew up in East London with a lot of Jamaicans, Nigerians, Indians, Bangladeshi, Polish, Lithuanians and British people so I picked up a lot) It definitely does impact your employability rate as you want to be as clear and thorough as possible in jobs depending how heavy the accent is Also level/yoe different working as an mle is not one I’ve seen. I understand that a MLE does not work only with the sexy machine learning models part, but also with all the CI/CD, migration to production, ML pipelines and all things related to automating the running of the model and training. In my experience, there are certain firms that are known for paying way above their competitors, and sometimes just to stop other firms from hiring the talent. Please delete this post if it is related to getting a job as a quant, causing with a change of being a quant, or getting the right training/education to be a quant. Should at least be possible to go from MLE to QD pretty easily, right? I think it’ll be easier for me to go from big tech ML -> QD than it would be for me to go from QD -> big tech ML if I decided to backtrack on the QD decision. How is it like the transition from big tech to top quant roles? Anyone who done this before can share their experience? so you mean to be DS/MLE at top tech company requires elite degree than quant at top hedge fund? I'm surprised. Most skills are transferable across modalities anyway I have some experience in prob/stats (usual high school level but also basic stochastic calculus, linear regression using OLS/MLE and standard Monte Carlo) because I had an investment analyst role (but not hardcore quant) before I started my PhD. I am planning to do something related to ML. 不确定做macro quant到底怎么样（和卷上天的equity stats arb比职业发展怎么样） In the end, a job in quant finance is never a given and forgoing multiple months of wages to study for quant recruiting cycle to potentially get a high paying job is risky. I have been studying coding a lot on my own, I have a decent (think like 2-3 undergrad courses) background in C++ and Python, a bit of Matlab and R, strong Math background – the first quarter of my freshman year I will be taking what’s considered sophomore-junior level math. I would also ideally be working internships/co-ops during the OMSCS. How much does median pay vs 90th percentile compares for sell vs buy side, for roughly 5 years of experience. We would like to show you a description here but the site won’t allow us. ML engineers at bank use ML for anti money laundering and marketing. true. I figure that SWE/quant is a possibility given the systems and math background that someone like an MLE would need to have anyway. As long as you open pnl as a quant, the sky is the limit. Quants use stats/ML to make money. fyi, TC growth is slower comparatively It is Not a CS program - I heard SWE and MLE prefer CS program. How much more variance is there in pay, on the sell side there's essentially no variance, quants at my bank don't go down in TC even when trading/sales goes down. The way you could criticize Reddit is that we weren't a company – we were all heart and no head for a long time. BPharma, Aerospace, or working in anything quant opens up those 300k/600 bucks an hour positions that people often associate with swe type dream jobs, but are in hilariously short supply and generally are in super hcol areas. So it appears that in Silicon Valley MLE tends to be what European companies will refer to as a (full stack) data-scientist. new grads are usually in the 200-250k range. As promised from an earlier post, here is an interview guide for quant positions (I've lost the original account due to bad memory with passwords - apologies if any conversations were cut off and feel free to continue them with this account). But I just wanna be some "regular" DS or MLE, because I'm interested in both coding and math. What exactly does an MLE do then . PhD quant here. Quant trader AMA: AMA by a quant trader. If it’s just supporting analytics workstreams, the pay will be worse than either MLE or SWE. there's more overlap in a back office quant role, but it's still not a big enough overlap to offset someone with the equivalent number of years in industry Hello everyone, I've been a full-stack developer for 4 years now, working extensively with (React/React native and JAVA). Im not sure it is worth the risk to apply to S&T over Quant Finance, since most BBs only let you submit 1 application, and I dont want to sabotage my chances of breaking into Markets broadly. DE depends on the role. MLE pays the most usually, there’s typically a premium on ML talent due to supply/demand. Data scientist certainly can be more software engineering focused but the title is thrown around mindless by so many companies that it can vary a lot, anywhere from being essentially an MLE job or a BI analyst job, or even a research scientist job. What's the worst part about being a quant dev or quant researcher? What's the best part? Dunno, I'm neither. I have a DE role and do what u/dmart89 describes as an MLE and do very little ETL work anymore, as an example. The mle document vs swe document at snap have the same year of experience expectations for different levels. highest guaranteed 1st year JS offer for a new grad i've seen was 900k in 2021 (expect lower for 2022+), which included sign on. I’ve done interviews at both G/FB, and those interviews were FAR easier than the HFT ones. I definitely want to pursue a career in data (data scientist, data engineer, MLE), but I’m also open to SWE or even quant. There's a community for whatever you're interested in on Reddit. At the first lag, which is lag= 0 (the big spike) the data you have is compared with an exact replica of itself, therefore the two datasets are equal, and perfectly correlated (1:1). not sure how it is at your school but at mine cs majors have training in probability theory, random processes such as ctmc and martingales, estimation theory (mle, map), linear algebra including matrix calculus and advanced la algorithms such as sparse PCA, optimization (lp, socp, etc), machine and deep learning You actually might even be a better candidate for quant, MLE, etc. Radix I know is famed for consistent ~500 post-phd offers, presumably other fanciest firms as well. in expectation, the ROI and opportunity cost with a PhD pales in comparison to a B. They make it by arbing ETF constituents vs the ETFs themselves. Reddit is a network of communities where people can dive into their interests, hobbies and passions. There are estoric nonlinear time series ones but they're hella niche and I don't have enough time in my life to dedicated to those. Additionally interviewers are going to expect you to be able to rattle off machine learning theory (statistics, optimization theory) or else the job you're interviewing for is to write code to speed up the work of the MLEs who work with the model and data. Master is not really good enough for a decent quant/MLE job. I think it would entail MLOps and also Data engineering? So like everything Obviously a company wont have all the roles . However, when looking for jobs, you'll seldom find a true "entry level" MLE, or MLOps positions. SWE roles ofc have a high degree of analytical work, but I get the impression is it less math based (on avg) and more system design / back-end heavy. Research engineering can be a lot of different things but at its core it’s about getting completed research projects into production and supporting them. Straight up stock price break a few of those assumptions. In many markets the spreads are miniscule so they add a lot of extra p&l by optimising funding rates across a range of derivatives and funding models to provide delta that is very close to holding the underlying basket. There are also many startups that recruit ex-quants though don't tend to offer the same magnitude of compensation packages as FAANG. ** Point 4: “Take home” salary vs gross salary** Quant positions have a high gross salary but they are usually in high cost of living areas. Recently, I've been captivated by the potential and challenges within the fields of Machine Learning (ML) and Data Science. I’m guessing if you want to work as a MLE or at FAANG you probably need to grind some, but none of the research-heavy DS or quant roles I’ve ever worked at used those in interviews. Companies tend to lean towards the more well known universities (UCT, Stellenbosch, Wits - in that order, from what I’ve seen). You can easily break into swe with applied math with the right internships/personal projects. People are leading you astray, CS has a ton of math and statistics in it. CSCareerQuestions protests in solidarity with the developers who made third party reddit apps. For MLE, DevOps/MLOps is the differentiator, whereas outside of full stack I’d argue that’s not really critical for DS. I work on AutoML for DNN specifically and worked in Ads before (auction; pricing algorithms). With all that being said, if I wanted to pivot from government research to finance with the ultimate goal of being a quant researcher, would trying to get my foot in The titles are so amorphous and non-specific (look at Spotify’s MLE roles, then Facebook’s, then a small startup’s DE JDs, then a FAANG one) that they’ll all exist and all ask for vastly different things, just like today. Check out heard on wall street and A Practical Guide to Quantitative Finance Interviews. Now moving to Finance there are many Quant researchers , quant Truly big money comes when you reach outlier levels of success for either paths, though I’d argue that you have a higher chance of getting capped lower in tech. You’re more likely to get hired as a CA / CFA / actuary over here. I'm currently a researcher but I used to work as an MLE (albeit on a more researchy team). 300k base pay is for experienced hires. 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. A friend of mine who got a 1st in comp sci from a Russel group got a quant role because he had already done multiple internships at the firm, but many others with similar qualifications weren't able to get quant roles at all. Eliminate factors such as institutional prestige, cost or alumni network, and simply look at statistics vs. you realize cs is a lot more then programming right. quite a few similar discussion there in the sub anyways. So I think it'd be really hard for me and for the team to kill Reddit in that way. Quant finance tends to be centered in particular cities (NYC, Chicago, HK, LND, etc) 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. sign on depends how much they want you. "MFEs are mostly cash cows and much easier to get into than CS PhDs" I totally agree. data Junior quant researcher at a buy-side finance firm pays ~400K+/year for new grads (includes guaranteed year-end bonus). So here is what the ACF (autocorrelation function) is telling you. A subreddit for the quantitative finance: discussions, resources and research. Yes, I don't have a PhD, only with CS master. Quant Analyst is generally a broad term, I've seen it used for "entry level" quant positions for firms, where they do a mix of everything until they decide to specialize. Would it make sense to switch to top tier quant funds? Quant Analyst in Model Val, 14 years experience mixed between QD, QA, in FO-adjacent role. Do quant devs just implement models that quant researchers make? Yes. I’d certainly rather be a FAANG executive vs being a quant, assuming equal pay. I've seen many ex-quants move to Facebook, Google, Amazon, and similar places. THAT PRETTY MUCH COMPLETES A CYCLE. SA doesn’t really have a quant industry/scene. 13 votes, 24 comments. I'm going to echo what u/peepspeepstoottoot said around higher risk / higher reward based on how close you are to alpha & monetization. Generally speaking, MLEs tend to be more software engineering focused. if you wanna break into quant trading, OMSCS is not really the type of program fitting well. I MLE interviews mostly still ask Leetcode questions, although they tend to be slightly easier than the ones for SWE. Reflections from a senior quant: a Reddit thread by a senior quant about careers in quant finance, in response to wrong information spread by students/users with no quant experience. sure, some firms would. There are many overlaps but what exactly will an MLE do. lol, every sub has its sub title: r/investing: losing money with friends . Idk tho Quant -> tech is starting to become a popular transition. 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. r/Economics: dismal science . My background: Pure math undergrad, quantitative PhD (one of math/CS/stats/physics), both at good If you are a graduate seeking advice that should have been asked in the megathread you may be banned if this post is judged to be evading the sub rules. not much. But do quants rely more on stats/complex math than ML/tech? I get that ML is also complex math in a way, but do they prefer say simple regression models, etc in comparison to state of the art ML/DL techniques? Nov 19, 2024 · I'm an MLE with PhD in ML. I think it is a result of the natural secrecy in this industry, combined with the unnatural bigger-than-average ego of quants Posted by u/tirarafuera1803 - 182 votes and 136 comments. I am an incoming MS student deciding between programs. Debating whether May 17, 2022 · IMO quant finance is great, but does depend on the company obviously. MFE itself didnt fit quant dev well, that's the stuff of CS. I currently have a BS in Mathematics from a state school and working on a MS in Computational Mathematics. I have a bit over 4 yoe with a T10 phd in a highly relevant field to finance. If you are really desperate to jump over ASAP, then apply as a grad but be warned you will need to do a lot of interview practice and will probably only talk in depth about ML in your final round. Personally, I suggest Meta. Personally, I always found Quant work more interesting because there is a stronger appreciation for stats/math. DA job market seems to be very bad for now. Quant trader is very competitive but you generally don't need advanced maths for it, they often hire fresh graduates. Apr 27, 2022 · MLE pros job security好 收入稳定 culture好. Quant dev is by and large a software engneer for some financia purpose. S. If it’s platform work, then it should be similar to regular SWE. What I am afraid is that I won't get any SWE job (because it is not a CS program) nor any MLE/Quant job (because it is just a master) I’m currently an E5 MLE at FAANG making pretty good money (500-600k). but that's like 10%-le (at least) quants, which given overall few hundred positions a year size of the quant market works out to. I would say that Machine Learning Engineers are actually sought after, but the demand can be sporadic and dependent on the specific industry. Hi! I am starting college this fall, majoring in Math-CS at UCSD. NLP vs audio vs vision vs robotics doesn’t really impact compensation. reddit's new API changes kill third party apps that offer accessibility features, mod tools, and other features not found in the first party app. ehhh. I am a Wall Street quant AMA: AMA by a Wall Street quant (very old, so some information might be out of date). r/quant: "You have no idea what you are talking about" . The top HFT and prop trading firms are out of reach for over 99% of developers. You’ll be lucky to make over 100K. Recently landed a "quant developer" offer at a small trading firm doing what seems like mostly data engineering (pipelines, warehouses etc. Stress should be another factor to consider. This was for a SWE position, and I’ve heard quant trader/researcher interviews are much harder. --难得的前台机会 不用转行 cons-baidu 1point3acres 压力大 风险高. Whereas data-scientists are frequently just "sql-monkeys" with light coding skills in silicon-valley. Meanwhile they will pay significantly more for high quality data analysts stateside - similar to non tech DS/MLE/DE salaries . I already hate those inapplicable case studies that some quant firms ask, last thing I need is inapplicable algorithmic brain teasers on top of that too:) Not personal experience but from what I've seen trying to get a quant role is hyper competitive. Didn't say that any of them is better or harder, it's a different skillset. Damn guys let’s help the guy, no need in shaming him. its probably one or two teams. Have ~7 yoe in tech working in ML, mostly production and infra but also some research work. Although I feel like I would be more likely to get interviews to these programs because of my more quantitative background and fewer applicants. this candidate had a competing offer from citadel HF. TLDR: Quant roles are more varied in what the work is like, but more math/stats heavy. From 1point 3acres bbs cons 很难再转回quant了，不确定自己有没有想好 PERM问题 QR pros. I am currently working as a Data Scientist but I would like to start learning the skills I need to become a MLE. expected bonus should be somewhere in the ball park of base pay for new grad. Don’t even try healthcare or government. " --Steve Huffman, CEO of Reddit, April 2023 Quantitative Portfolio/Investment/Asset Manager: New and may not become a role Found in investment funds, asset management, and investment management Requires long-term quant experience (preferably on the buy-side) Annual Total Compensation: $250,000+ Low Stability Medium WLB High Stress High Prestige Just a thing to note , global companies (atleast in my industry) will hire the DS and DE AND MLE jobs abroad … for less $$$ than stateside but still excellent pay for that country . SDE vs MLE I'm currently working as a quant researcher in India since 3 years and want to switch my field because most of the modelling work is done by PHDs in US and we're mostly implementing and testing their models. Most guys end up being quant analysts at banks / consulting at KPMG, etc. 73K subscribers in the quant community. You wrote in another comment: As a MLE I want to build models. Take ML focused classes at a college that can actually provide it. This is because these positions are relatively "new" posts, and like all "new" positions they're somewhat "exclusive" to usually 2+ YoE (Years of doing something more akin to Da You do return for financial data because most time series model have assumptions. Prior that I was in the military (got out and made the switch to DS/MLE). if you wanna be a quant dev, OMSCS fits well. Yoe tends to be pretty stable requirement for level across swe types. . My experience is limited to the Autonomous Vehicle (AV) industry so take that for what it is. What criteria does your quant fund use to hire quants? You need a Math/Physics/Stats/CS PhD from a top school. in STEM + 5 years as a quant. ). Two Sigma just doesn't pay enough to warrant tech vs quant For reference, Two Sigma first year pay is decent (slightly higher than FB at 325) but does not scale in the same way as JS/HRT/Cit/Jump, their pay is based on levels and is on levels. However, it's not advanced knowledge, nothing like machine learning or university level statistics. - DE is at the base of most of the data use cases, while MLE is for a smaller subset - MLE solutions are usuually complex and do not generate revenue quick enough to be seen as a ""safe" investment. mbgemxt vekygbdfy jmoeogx ugbldg qjnv tihttrw wod anug tygzwmff bvv tcptmm heodv jgmz zsxzd fzlt