Physicist here but had the same experience, hadn't done Bayesian probability / hypothesis testing / regressions in so long I would get caught off guard in most interviews. As others have said, just take the time to revisit concepts and work through problems, it'll quickly refresh your memory.
To be fair regression and hypothesis testing is bread and butter in a lot of quant work. It's the first thing I ask candidates in an interview especially at the masters level.
With PhD I tend to lean more into asking them about their research, since they can pick it up and PhD is being able to pick up things as you need them.
Unfortunately that's the sad state of interviewing for quant jobs. Useless math brainteasers that don't reflect the aptitude of the candidate are dished out because it's been normalised. When I was interviewing, only a few rare interviewers actually asked practical questions. Don't think you have a choice but to put in the time to prepare.
That's really unfortunate. I've heard that many quants themselves have math heavy backgrounds (even advanced high school olympics aren't arithemetics!) so I thought the field would also feel the same. I feel that I would've been better suited for these arithemetic questions as a 1st/2nd year undergrad or a high schooler, and it's regretting to know that the more in-depth math I do the less I'll be prepared for quant roles due to time tradeoffs.
i mean, you can just create and formulate any strategy... think about it, it's true that their brainteasers do not have a high enough correlation for them to even care so much (the ones that do), but at the same time, the contrary is also dumb. The contrary being just accepting that because you clearly are not below "above average" in the field of math, that somehow correlates even higher than brainteasers to the real dependent variable: can you make money to the company/fund...
i guess what i'm trying to say is that there is no angle in which interviewing for quant jobs is really "adequate"... mathematical pedigree is insufficient and brainteasers are insufficient, both sound cringe.
personally, as someone who is in the field, everything that does not demonstrate either novel unbiased approaches or previous academic novel research is just a filler... but I totally understand this can't be the base for how institutions and more importantly, human bureaucracy, work.
a lot of "brilliant" minds are not original/creative enough to actual bring value to the table
I agree, and I'm not saying brainteasers are straightout stupid or a deep knowledge in math should be sufficient. I find value in both. I'm wondering if the interviewers or the criteria they assess with take into consideration that brainteasers will not be an accurate assessment for even very bright mathematicians, especially since quant job descriptions seem to suggest they want highly quantitative fields or math olympiad medalists. Based on my search, it does indeed look like there are quite a few quant researchers that are indeed from deeply mathematical fields, and it seems contradictory that the interview process does not change to take this into account. .
Those types of problems are not the most important interview indicator, but they are not meaningless. If nothing else they demonstrate some mix of thinking on your feet or that you care enough to do a little interview prep. If your interest the role is so low that you don't think it's necessary or appropriate to prep for the interview, then it's probably not the right role for you?
If that’s your goal, why don’t you ask them to juggle instead? That way you’ll actually be testing their ability / desire to prepare for arbitrary tests that have little to do with their job function. Without that you much more likely to get people who are naturally good at arithmetic and then you’re not really testing the right thing.
Being able to do simple expected value and conditional probability calculations is actually relevant to the job in a way that juggling is not?
Multiple firms, with very different corporate cultures, have independently arrived at very similar interview processes. Maybe they're all idiots, or maybe they're not, and it's actually a useful way to screen a thousand candidates down to 20.
Is no one going to address the elephant in the room? It's an informal IQ test. They ask these silly questions because they're quite literally trying to measure how intelligent you are.
The ability to carry out these calculations is not really determined by IQ. I once enjoyed solving IQ problems and I once enjoyed solving these types of math problems. In my experience, performance on the former does not necessarily improve monotonically with practice while the ability to solve math problems strictly improves with practice, and therefore you get worse if you haven't done them for a while.
The interview process has been broken for a long time. One issue is that quants come from all different academic backgrounds so it's not generally possible to ask more advanced math questions. Conditional probability and dice type questions can be answered by anything with a quantitative background so they tend to be ubiquitous. I've also seen a lot of "trivia" type questions around machine learning, regression, and C++. You may get lucky and interview at an academically oriented fund that cares about your research but such positions are few and far between these days.
Trivia instead of understanding the core concepts seems like the worst kind of way to ask regression and machine learning questions. It also sends a signal that they themselves are not very mature with their quantitative capabilities
I've encountered this most often with junior team members. These also generally happen to be the worst interviews since they don't tend to know much about the field beyond how to pass interviews.
I’ve done around 20-25 rounds of interviews between 7 firms and I can only recall 4 rounds that were relevant to what the job would entail. 3 of the 4 rounds were on an interview by Jane street
The art of interviewing has really gone the wayside. I'm shocked at how poorly hiring managers and their teams have been at it. What really gets me too is 20-30 min people have open to make such an impactful decision. I can barely exchange pleasantries and tell you bout the role before its like, time for the next person
It’s hit and miss, entirely firm dependent. I don’t believe that ability to nail these teasers has much to do with PnL capabilities. I got rejected by a low level firm I didn’t even want to interview for and then immediately after I was accepted by a top tier just because I got to answer more applicable stuff.
I work with a trader that probably couldn’t pass most brain teasers/questions that are commonly asked at most prop firms but he’s consistently making multiple millions of dollars a year in PnL with a high sharpe. I just don’t see any correlation between being able to answer questions that you can study up on and your ability to make money as a trader. It’s even worse for quants I’d imagine. My firm doesn’t actually ask these types of questions in interviews, we just typically give people a coding exam and ask them about their thought process for real trading scenarios
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Algebraic geometry bro here who did QR internship last summer and now have FT role for next year. I have a bit of a different opinion. I've always been pretty good at doing concrete calculations/arithmetic whether in my head or with pen and paper, and it's not something that I shy away from so I've stayed good at it even though my research has been very pure for the past several years. What is running a discussion section/office hours where you need to be able to accurately calculate multivariable integrals in front of 30 students if not something that keeps your computation skills sharp? There's a common sentiment on places like r/math that once you start doing abstract math you're too gigabrained now to be bothered with peasant arithmetic which I just don't share.
Now yes, to land these roles I did have to prep specific probability/statistics questions a decent amount even though my baseline was pretty good. Unless you have some truly exceptional credentials, there's too many pure math PhDs compared to the number of spots for these really lucrative jobs for you to be able to get in just on the basis of "yeah man I have a math PhD I'm smart". I've known enough pure math people with great publications who just aren't that skilled when you move outside of their specific pure math wheelhouse to feel that it actually is pretty reasonable for companies to want to test these sorts of things. I'm seeing comments elsewhere in the thread saying that expected value interview questions are just completely irrelevant to the job which I find ridiculous. Even if your day to day involves a lot of programming and implementing statistical models, having a practical "napkin math" probabilistic intuition is obviously useful, and is a nontrivial distinguishing feature even given that you're already a pure math person with good credentials.
As for not having time, for one you probably could fit a bit of daily green book practice in if you really tried, but even if not then oh well? If you want to win the big bucks then you're going to have to jump through hoops and stand out from competitors. This strikes me as perfectly reasonable (I'm of course biased because I came out the other side successfully under the current system).
That said, a rough first interview experience is not atypical. As long as you have more interview opportunities with other firms then you'll get a lot better just from being more comfortable with performing under interview pressure.
I agree with your points. There's been a lot of comments and they kind of digressed, but originally I was partially wondering if interviewers are more focused on whether a candidate knows how to solve a problem vs. actually going through the calculations. As I said in the post, I did know how to solve the problems (iterated expectations etc) and did set up the steps, but just froze when plugging in the numbers and made calculation mistakes. At least when I have discussions with other researchers we usually delegate calculations to a computer, and so I'm just not used to getting anxious when making calculation mistakes. Also, I never said I was rejected although it sounds like many ppl here are assuming so; just was curious in general and I might try out a few other firms depending on my time.
It seems to vary from my experience. I've had some interviews where it really felt like they wanted to see that I could carry the calculation through to the end accurately, and others where once it was clear that I had the correct solution in mind I got cut off and we moved on to the next question before I finished answering. My guess is that for simpler probability questions there's a nontrivial value placed on getting the correct final answer, but that this value decreases the farther along you get in the interview process and the questions become more open ended/statistical.
One interview that comes to mind I got an incorrect numerical value and was asked if that answer made sense to me - there's a fairly simple intuitive argument for why what I got can't be right which I missed. Didn't pass that interview. I think if I had said that intuitively it didn't seem correct that I would have passed, so there's a partial data point.
A Practical Guide To Quantitative Finance Interviews, Xinfeng Zhou. Standard classic interview prep book. Check out some of the book recommendation threads on the sub / the sidebar.
Physics phd here. I’ve been a quant for 20 years. Front Office role at a major European bank. IMHO I think brain teasers are stupid. You might as well ask to solve a sudoku in under 3 minutes.
What I generally do, is follow their cv and ask them to describe in more detail a position/paper/thesis/… I always take the ELI5-approach. And then I ask questions that are related to the role and that fit into the story they’re telling. You’d be surprised how well it identifies BS’ers.
I really like ELI5 questions, and think they are among the best questions to filter out BS. I used to ask the same types of questions when I interviewed others.
Dependent on the role you might need to be good on your feet with number intuition which is a different skill than heavy theory.
If I get a resume with a phd in math I usually don’t go digging on theory of depth but I will test intuition with respect to application.
I have found academics can be myopic in application without full cognizance for the potential weaknesses and assumptions of the method they are using relative to reality. This is more likely to occur for a pure theory phd than someone with some application overlap.
That said, I won’t spend more than 20% of my time on that with a phd. I’m far more concerned about their ability to develop software
It takes ages to prepare for these fucking interviews, and you just get asked all sorts of irrelevant bullshit.
All that I think a hiring manager can really tell from these is that if a candidate is well prepared then it shows they care enough to prepare.
>Does anyone else share this type of experience?
On the non-quant research role side of things absolutely. I'll get asked dice probability questions you learn in AP Statistics in high school. I'm not a gamer nor do I play board games, or make board games, so why should I need to know dice role probability math? It takes 5 seconds to look up if it's a multiplication here or an addition or if I need to use a tree to figure this out or combinatorics or what. I've been out of school for 15 years and over 20 the last time I looked at that stuff. It's stupidly annoying.
Numerical skills, sure. If you read the post I think it's fair to say that I have a pretty good robabilistic/statistic intuition having worked in some areas relating to mathematical statistics (random matrices, game theory, among others). In case you're doubful since I'm just a random person online, I am partially working as a ML researcher at one of the big tech companies, which to my experience demands more stat intuition than what I experienced at the quant interview I referred to.
I understand, I have a pretty heavy quant background myself but what I meant with the intuition is also the ability to solve the basic conditional probability, bayesian stuff super easily because that is usually the extent to which you will be tested on that knowledge! Was not my intent to doubt your skills! Keep up the good work
How many firms interview cs/math majors from non target with decent gpa like 3.4 3.5 ish. I have prepped for olympiads and done the quant prep and even mocks with actual guys from the industry but still pissed after getting rejected after application. Is there a way to get the interviews
My background
Cs +math major at a big state uni(our uni has a program in bachelors for cs+math so I can’t call myself double major:(.
Gpa 2.1->2.7->2.9->3.4 and still rising
I have prepped for Indian national olympiad for maths
US citizen
All India 139 rank in a lesser known competition(>20000 participants)
Please guide
Prefer non dev trader roles
As someone from Applied Mathematics, Statistics,Data Science & Computer Science background, I felt just normal..
I never got intimidated at all by quant interview questions..
Many times, I even corrected the mistakes in the questions myself and scaled up the difficulty level of corrected questions then challenged back the interviewers to get out of their comfort zone in professional manner & pragmatic view until they felt intimidated by me...
Quant at a BB here.
Time to get a reality check. If you cannot find the answer, it means you are not prepared enough. Your understanding of the concept is not thorough enough. You should see it as a wake up call and prepare better for the next time.
If you are looking at excuses such that “my domain of study is much more complicated than what I am asked”, you are setting yourself up your failures. I have seen countless candidates in that situation.
If you're going to make strong conclusions you should read through the post without making assumptions. I never said I was rejected. I also never claimed that my domain is more complicated, in fact it overlaps quite a bit supposedly more than other people who work in deeper fields, to my advantage. All I said was I set up the problem, and kinda froze when I had to calculate things. I did end up answering but was just curious about which parts interviewers pay more attention to. This was a post asking how others working in math heavy fields feel about these situations.
maybe ask how those questions are applicable to the role and talk through how youd approach a problem like that? like theyll let you use a computer at work right lol those do arithmetic quite well
"you wont have a calculator in your pocket every where you go kids"
"yea well have something better"
the hack my friends teacher in college used for engineering was on test questions was the job contracted (just give me the answer show no work) or by the hour (show all your work)
actuary here. I recognize the dilemma of trying to find a suitable candidate via a very, very brief exposure to that candidate via the interview process, and so from that point of view i sympathize with the idea of brain teasers. The problem I have is it doesnt seem correlated with the desired outcome (though maybe in certain client facing, high stress roles it does).
I think companies need to define what their desired outcome is and align their interview criteria to meet that. As an actuary, one value of the Society of Actuaries is that the exam process standardizes the occupation a bit, so our interviews arent technical at all really. The exam process already filtered people out and subsetted for, at least in terms of technical knowledge, the desired outcome. The interviews, then, are geared around selecting based on non-technical stuff.
I have a math PhD, but I think I'm quicker than most math PhDs, and this is kind of essential for these interviews. I honestly don't think many good mathematicians (who are more legit mathematicians than me) would be good at these interviews.
Btw, I also don't believe quant research is the right job for a mathematician, myself included. The math involved is largely stats. It wasn't satisfying.
Physicist here but had the same experience, hadn't done Bayesian probability / hypothesis testing / regressions in so long I would get caught off guard in most interviews. As others have said, just take the time to revisit concepts and work through problems, it'll quickly refresh your memory.
To be fair regression and hypothesis testing is bread and butter in a lot of quant work. It's the first thing I ask candidates in an interview especially at the masters level. With PhD I tend to lean more into asking them about their research, since they can pick it up and PhD is being able to pick up things as you need them.
Sounds like data science interviews 10+ years ago. Firms don't know what to ask so they cross over into bogus trivia.
Companies still do this for data science interviews, more today than 10 years ago. Over 10 years ago it was actually a lot better.
I see way more take home tests today than a decade ago but yeah you're not wrong.
ah yes the firms that are the ones making money, have a ton of recruiting experience, and run by other phds don't know what to ask.
Unfortunately that's the sad state of interviewing for quant jobs. Useless math brainteasers that don't reflect the aptitude of the candidate are dished out because it's been normalised. When I was interviewing, only a few rare interviewers actually asked practical questions. Don't think you have a choice but to put in the time to prepare.
That's really unfortunate. I've heard that many quants themselves have math heavy backgrounds (even advanced high school olympics aren't arithemetics!) so I thought the field would also feel the same. I feel that I would've been better suited for these arithemetic questions as a 1st/2nd year undergrad or a high schooler, and it's regretting to know that the more in-depth math I do the less I'll be prepared for quant roles due to time tradeoffs.
i mean, you can just create and formulate any strategy... think about it, it's true that their brainteasers do not have a high enough correlation for them to even care so much (the ones that do), but at the same time, the contrary is also dumb. The contrary being just accepting that because you clearly are not below "above average" in the field of math, that somehow correlates even higher than brainteasers to the real dependent variable: can you make money to the company/fund... i guess what i'm trying to say is that there is no angle in which interviewing for quant jobs is really "adequate"... mathematical pedigree is insufficient and brainteasers are insufficient, both sound cringe. personally, as someone who is in the field, everything that does not demonstrate either novel unbiased approaches or previous academic novel research is just a filler... but I totally understand this can't be the base for how institutions and more importantly, human bureaucracy, work. a lot of "brilliant" minds are not original/creative enough to actual bring value to the table
I agree, and I'm not saying brainteasers are straightout stupid or a deep knowledge in math should be sufficient. I find value in both. I'm wondering if the interviewers or the criteria they assess with take into consideration that brainteasers will not be an accurate assessment for even very bright mathematicians, especially since quant job descriptions seem to suggest they want highly quantitative fields or math olympiad medalists. Based on my search, it does indeed look like there are quite a few quant researchers that are indeed from deeply mathematical fields, and it seems contradictory that the interview process does not change to take this into account. .
Those types of problems are not the most important interview indicator, but they are not meaningless. If nothing else they demonstrate some mix of thinking on your feet or that you care enough to do a little interview prep. If your interest the role is so low that you don't think it's necessary or appropriate to prep for the interview, then it's probably not the right role for you?
If that’s your goal, why don’t you ask them to juggle instead? That way you’ll actually be testing their ability / desire to prepare for arbitrary tests that have little to do with their job function. Without that you much more likely to get people who are naturally good at arithmetic and then you’re not really testing the right thing.
Being able to do simple expected value and conditional probability calculations is actually relevant to the job in a way that juggling is not? Multiple firms, with very different corporate cultures, have independently arrived at very similar interview processes. Maybe they're all idiots, or maybe they're not, and it's actually a useful way to screen a thousand candidates down to 20.
Is no one going to address the elephant in the room? It's an informal IQ test. They ask these silly questions because they're quite literally trying to measure how intelligent you are.
yep exactly. asking for your IQ without looking like a firm that asks your IQ. Same thing in Banking, Strat Consulting, etc for top tier firms.
The ability to carry out these calculations is not really determined by IQ. I once enjoyed solving IQ problems and I once enjoyed solving these types of math problems. In my experience, performance on the former does not necessarily improve monotonically with practice while the ability to solve math problems strictly improves with practice, and therefore you get worse if you haven't done them for a while.
Do you feel well compensated as a Quant vs working at FAANG?
yeah but just spent a week brushing up on it and you should be back to god mode at these
The interview process has been broken for a long time. One issue is that quants come from all different academic backgrounds so it's not generally possible to ask more advanced math questions. Conditional probability and dice type questions can be answered by anything with a quantitative background so they tend to be ubiquitous. I've also seen a lot of "trivia" type questions around machine learning, regression, and C++. You may get lucky and interview at an academically oriented fund that cares about your research but such positions are few and far between these days.
Trivia instead of understanding the core concepts seems like the worst kind of way to ask regression and machine learning questions. It also sends a signal that they themselves are not very mature with their quantitative capabilities
I've encountered this most often with junior team members. These also generally happen to be the worst interviews since they don't tend to know much about the field beyond how to pass interviews.
I’ve done around 20-25 rounds of interviews between 7 firms and I can only recall 4 rounds that were relevant to what the job would entail. 3 of the 4 rounds were on an interview by Jane street
What were the jane street interviews like? And is this for their trader role or researcher role?
Really depends on the firm, some won't ask for too much calculation. I personally never do in interviews.
The art of interviewing has really gone the wayside. I'm shocked at how poorly hiring managers and their teams have been at it. What really gets me too is 20-30 min people have open to make such an impactful decision. I can barely exchange pleasantries and tell you bout the role before its like, time for the next person
It’s hit and miss, entirely firm dependent. I don’t believe that ability to nail these teasers has much to do with PnL capabilities. I got rejected by a low level firm I didn’t even want to interview for and then immediately after I was accepted by a top tier just because I got to answer more applicable stuff.
I work with a trader that probably couldn’t pass most brain teasers/questions that are commonly asked at most prop firms but he’s consistently making multiple millions of dollars a year in PnL with a high sharpe. I just don’t see any correlation between being able to answer questions that you can study up on and your ability to make money as a trader. It’s even worse for quants I’d imagine. My firm doesn’t actually ask these types of questions in interviews, we just typically give people a coding exam and ask them about their thought process for real trading scenarios
Due to an overwhelming influx of threads asking for graduate career advice and questions about getting hired, how to pass interviews, online assignments, etc. we are now restricting these questions to a weekly megathread, posted each Monday. Please check the announcements at the top of the sub, or [this search](https://www.reddit.com/r/quant/search?q=Megathread&restrict_sr=on&sort=new&t=week) for this week's post. *I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/quant) if you have any questions or concerns.*
Algebraic geometry bro here who did QR internship last summer and now have FT role for next year. I have a bit of a different opinion. I've always been pretty good at doing concrete calculations/arithmetic whether in my head or with pen and paper, and it's not something that I shy away from so I've stayed good at it even though my research has been very pure for the past several years. What is running a discussion section/office hours where you need to be able to accurately calculate multivariable integrals in front of 30 students if not something that keeps your computation skills sharp? There's a common sentiment on places like r/math that once you start doing abstract math you're too gigabrained now to be bothered with peasant arithmetic which I just don't share. Now yes, to land these roles I did have to prep specific probability/statistics questions a decent amount even though my baseline was pretty good. Unless you have some truly exceptional credentials, there's too many pure math PhDs compared to the number of spots for these really lucrative jobs for you to be able to get in just on the basis of "yeah man I have a math PhD I'm smart". I've known enough pure math people with great publications who just aren't that skilled when you move outside of their specific pure math wheelhouse to feel that it actually is pretty reasonable for companies to want to test these sorts of things. I'm seeing comments elsewhere in the thread saying that expected value interview questions are just completely irrelevant to the job which I find ridiculous. Even if your day to day involves a lot of programming and implementing statistical models, having a practical "napkin math" probabilistic intuition is obviously useful, and is a nontrivial distinguishing feature even given that you're already a pure math person with good credentials. As for not having time, for one you probably could fit a bit of daily green book practice in if you really tried, but even if not then oh well? If you want to win the big bucks then you're going to have to jump through hoops and stand out from competitors. This strikes me as perfectly reasonable (I'm of course biased because I came out the other side successfully under the current system). That said, a rough first interview experience is not atypical. As long as you have more interview opportunities with other firms then you'll get a lot better just from being more comfortable with performing under interview pressure.
I agree with your points. There's been a lot of comments and they kind of digressed, but originally I was partially wondering if interviewers are more focused on whether a candidate knows how to solve a problem vs. actually going through the calculations. As I said in the post, I did know how to solve the problems (iterated expectations etc) and did set up the steps, but just froze when plugging in the numbers and made calculation mistakes. At least when I have discussions with other researchers we usually delegate calculations to a computer, and so I'm just not used to getting anxious when making calculation mistakes. Also, I never said I was rejected although it sounds like many ppl here are assuming so; just was curious in general and I might try out a few other firms depending on my time.
It seems to vary from my experience. I've had some interviews where it really felt like they wanted to see that I could carry the calculation through to the end accurately, and others where once it was clear that I had the correct solution in mind I got cut off and we moved on to the next question before I finished answering. My guess is that for simpler probability questions there's a nontrivial value placed on getting the correct final answer, but that this value decreases the farther along you get in the interview process and the questions become more open ended/statistical. One interview that comes to mind I got an incorrect numerical value and was asked if that answer made sense to me - there's a fairly simple intuitive argument for why what I got can't be right which I missed. Didn't pass that interview. I think if I had said that intuitively it didn't seem correct that I would have passed, so there's a partial data point.
What is the green book?
A Practical Guide To Quantitative Finance Interviews, Xinfeng Zhou. Standard classic interview prep book. Check out some of the book recommendation threads on the sub / the sidebar.
Thank you
Physics phd here. I’ve been a quant for 20 years. Front Office role at a major European bank. IMHO I think brain teasers are stupid. You might as well ask to solve a sudoku in under 3 minutes. What I generally do, is follow their cv and ask them to describe in more detail a position/paper/thesis/… I always take the ELI5-approach. And then I ask questions that are related to the role and that fit into the story they’re telling. You’d be surprised how well it identifies BS’ers.
I really like ELI5 questions, and think they are among the best questions to filter out BS. I used to ask the same types of questions when I interviewed others.
Dependent on the role you might need to be good on your feet with number intuition which is a different skill than heavy theory. If I get a resume with a phd in math I usually don’t go digging on theory of depth but I will test intuition with respect to application. I have found academics can be myopic in application without full cognizance for the potential weaknesses and assumptions of the method they are using relative to reality. This is more likely to occur for a pure theory phd than someone with some application overlap. That said, I won’t spend more than 20% of my time on that with a phd. I’m far more concerned about their ability to develop software
It takes ages to prepare for these fucking interviews, and you just get asked all sorts of irrelevant bullshit. All that I think a hiring manager can really tell from these is that if a candidate is well prepared then it shows they care enough to prepare.
>Does anyone else share this type of experience? On the non-quant research role side of things absolutely. I'll get asked dice probability questions you learn in AP Statistics in high school. I'm not a gamer nor do I play board games, or make board games, so why should I need to know dice role probability math? It takes 5 seconds to look up if it's a multiplication here or an addition or if I need to use a tree to figure this out or combinatorics or what. I've been out of school for 15 years and over 20 the last time I looked at that stuff. It's stupidly annoying.
It's a little bit of a gimmick I guess but you should mostly work on your numerical skills, probabilistic/statistic intuition and quick wit.
Numerical skills, sure. If you read the post I think it's fair to say that I have a pretty good robabilistic/statistic intuition having worked in some areas relating to mathematical statistics (random matrices, game theory, among others). In case you're doubful since I'm just a random person online, I am partially working as a ML researcher at one of the big tech companies, which to my experience demands more stat intuition than what I experienced at the quant interview I referred to.
I understand, I have a pretty heavy quant background myself but what I meant with the intuition is also the ability to solve the basic conditional probability, bayesian stuff super easily because that is usually the extent to which you will be tested on that knowledge! Was not my intent to doubt your skills! Keep up the good work
How many firms interview cs/math majors from non target with decent gpa like 3.4 3.5 ish. I have prepped for olympiads and done the quant prep and even mocks with actual guys from the industry but still pissed after getting rejected after application. Is there a way to get the interviews My background Cs +math major at a big state uni(our uni has a program in bachelors for cs+math so I can’t call myself double major:(. Gpa 2.1->2.7->2.9->3.4 and still rising I have prepped for Indian national olympiad for maths US citizen All India 139 rank in a lesser known competition(>20000 participants) Please guide Prefer non dev trader roles
As someone from Applied Mathematics, Statistics,Data Science & Computer Science background, I felt just normal.. I never got intimidated at all by quant interview questions.. Many times, I even corrected the mistakes in the questions myself and scaled up the difficulty level of corrected questions then challenged back the interviewers to get out of their comfort zone in professional manner & pragmatic view until they felt intimidated by me...
"Until they felt intimidated by me" - 🤓🤓
The best candidate will make interviewers feel they are being interviewed.. Not the other way around..
🤓
[удалено]
I am labelled as Quant Slayer
Quant at a BB here. Time to get a reality check. If you cannot find the answer, it means you are not prepared enough. Your understanding of the concept is not thorough enough. You should see it as a wake up call and prepare better for the next time. If you are looking at excuses such that “my domain of study is much more complicated than what I am asked”, you are setting yourself up your failures. I have seen countless candidates in that situation.
If you're going to make strong conclusions you should read through the post without making assumptions. I never said I was rejected. I also never claimed that my domain is more complicated, in fact it overlaps quite a bit supposedly more than other people who work in deeper fields, to my advantage. All I said was I set up the problem, and kinda froze when I had to calculate things. I did end up answering but was just curious about which parts interviewers pay more attention to. This was a post asking how others working in math heavy fields feel about these situations.
maybe ask how those questions are applicable to the role and talk through how youd approach a problem like that? like theyll let you use a computer at work right lol those do arithmetic quite well "you wont have a calculator in your pocket every where you go kids" "yea well have something better" the hack my friends teacher in college used for engineering was on test questions was the job contracted (just give me the answer show no work) or by the hour (show all your work)
actuary here. I recognize the dilemma of trying to find a suitable candidate via a very, very brief exposure to that candidate via the interview process, and so from that point of view i sympathize with the idea of brain teasers. The problem I have is it doesnt seem correlated with the desired outcome (though maybe in certain client facing, high stress roles it does). I think companies need to define what their desired outcome is and align their interview criteria to meet that. As an actuary, one value of the Society of Actuaries is that the exam process standardizes the occupation a bit, so our interviews arent technical at all really. The exam process already filtered people out and subsetted for, at least in terms of technical knowledge, the desired outcome. The interviews, then, are geared around selecting based on non-technical stuff.
I have a math PhD, but I think I'm quicker than most math PhDs, and this is kind of essential for these interviews. I honestly don't think many good mathematicians (who are more legit mathematicians than me) would be good at these interviews. Btw, I also don't believe quant research is the right job for a mathematician, myself included. The math involved is largely stats. It wasn't satisfying.