How to Get a Quant Job in Finance

https://www.financejobs.co/development/how-to-get-a-quant-job-in-finance.html

by saraha • 12 years ago

179 140 12 years ago

ivanche• 12 years ago

" Brainteasers are popular." Can somebody explain why? I'm genuinely interested, since in software dev interviews we see less and less brainteasers...

busterarm3• 12 years ago

Hedge funds have a hard-on for these kind of questions regardless of the role. I got a few of them in the interviews I had for the one I did IT support for...

They also liked taking Ivy grads with BAs and giving them receptionist jobs.

tormeh2• 12 years ago

It's the perfect market at work, I tell you. The private industry can do no wrong because then people would stop investing in the company and/or stop buying their services.

throwaway283719• 12 years ago

One (slightly cynical) answer is that people like to hire people like them. Most quant types working in hedge funds are very good at brainteasers, and if other people are good at brainteasers it ticks one of the "this person is like me" boxes whilst also ticking the "this person is smart" box.

It also allows an endless pissing contest of comparing new brainteasers among your colleagues, and telling stories of helpless candidates who couldn't even manage the first gasp of a hint of an idea towards the solution.

I tend not to like extremely complex brainteasers as interview questions, and especially not ones that require an "aha" moment to solve them correctly, because mostly what you're testing for is whether the candidate has seen that question before (or one like it).

On the other hand, I am a big fan of asking relatively easy math questions (i.e. first year undergraduate) in interviews, because if I'm going to be paying someone $100k+ to work on mathematical models, I'm damn well going to make sure that they understand basic probability, statistics, calculus and linear algebra. These are a bit like fizz-buzz for quants - if the candidate can answer them it doesn't prove anything, but if they can't answer them then you can stop the interview right there.

stupandaus• 12 years ago

Brainteasers are somewhat common in consulting interviews (at the undergraduate level). The idea behind giving brainteasers is more to see how you would structure and break down a problem, and whether you can communicate your structure and solution effectively.

murbard210• 12 years ago

I work as a quant and I like to give brainteasers in interview. It definitely does not tell me if someone will necessarily be good at his job or a good fit for the team, but it does help me rule out a lot of potential candidates.

These are not very tricky brainteasers that depend on getting a particular insight. They're actually somewhat pedestrian. However, if you can't manage to competently work out a simple, well defined problem, you're going to struggle with the more complex issues we deal with.

waterlesscloud• 12 years ago

Can you give an example or two of the more complex issues you deal with?

I honestly have no idea.

mlrtime2• 12 years ago

Interviewers are (should) not interested in the correct answer. They are interested in seeing the candidate think out loud. They want to see how you start tackling difficult problems.

Hansi4• 12 years ago

I second this, we almost never use brainteasers but they can be useful for seeing how people think about solving problems. Once people have 2+ years of experience it becomes less relevant because it's more useful to talk about actual work they've done rather than some puzzles.

vijucat• 12 years ago

It's a shibboleth : https://en.wikipedia.org/wiki/Shibboleth. It shows you belong.

jim_greco• 12 years ago

In my experience in finance it's all about the interviewer showing the interviewee how smart she is.

There's smart quants/programmers/traders/etc and people good at solving brainteasers. You need the former, but people who use brainteasers in the interview process typically only find the small sliver of overlap in the venn diagram.

silverbax882• 12 years ago

Brainteasers in an interview is a red flag that you probably don't want to work for the company. In my experience.

If you're interviewing someone and you're lazy enough (or not confident enough) in your skills at assessing a candidate, that's a weakness.

Rainymood• 12 years ago

Interesting!

Thanks a lot for writing/posting this. I enjoyed the read.

One thing I had to chuckle at was this:

Mark Joshi obtained a B.A. in mathematics (top of year) from the University of Oxford in 1990, and a Ph.D. in pure mathematics from the Massachusetts Institute of Technology in 1994. He was an assistant lecturer in the department of pure mathematics and mathematical statistics at Cambridge University from 1994 to 1999. Following which he worked for the Royal Bank of Scotland from 1999 to 2005 as a quantitative analyst at a variety of levels, finishing as the Head of Quantitative Research for Group Risk Management. He joined the Centre for Actuarial Studies at the University of Melbourne in November 2005 as an associate professor and is now a full professor.

Pure math to quant to actuary. It's kind of funny how I see/have met so many people that have gone this route. It's like they got sucked into pure mathematics, then thought: shoot I really need to get some practical work done with this math! And afterwards, at a later stage in life they wanted to back out and wanted a stable, high paying, but still math heavy job (actuary!).

Does anybody here have any experiences with being on the 'front office'? I'd love to hear them.

zerr• 12 years ago

And also theoretical physicists. Permanent jobs are hard to find in these domains...

mdda2• 12 years ago

What's the upside to admitting on HN to having front office experience?

skrebbel• 12 years ago

Seriously? Why are you on HN at all?

lotsofmangos• 12 years ago

"Following which he worked for the Royal Bank of Scotland from 1999 to 2005 as a quantitative analyst at a variety of levels, finishing as the Head of Quantitative Research for Group Risk Management."

No wonder he moved to Australia.

branchless3• 12 years ago

Pure math to head of QR risk management over the period when RBS took on insane leverage and relied on wholesale lending markets staying at low rates forever. An assumption that was incorrect and led to RBS being bailed out by UK tax-payers.

Good work fella.

shamney• 12 years ago

head of quantitative research = spending all your time on pricing models for complex derivatives. it's unlikely he had anything to do with RBS's overall financial strategy

dreamweapon7• 12 years ago

But hey, it must have been a fun, taxpayer-subsidized ride. Or as a certain person in the industry once famously said: "As long as the music's playing, you've got to get up and dance", right?

walshemj• 12 years ago

should have paid more attention to the machines in the dinosaur pen :-)

For non uk peeps a while back RBS had major screw up on the mainframe side that meant that some people where not able to access their bank account for days weeks for one of the NI subsidiary's

bradleyjg• 12 years ago

My great-uncle went pure math (he had an Erdős number of 1), a brief sojourn in industry, pure math.

From the stories I've heard the industry stint was purely about money. He had grown up very poor and had four children, a few years working on oil field and bond models was enough to supplement his professor salary for the rest of his career.

On the other extreme is someone like Simons who left pure math to found a hedge fund and is still at it billions of dollars later.

azmenthe• 12 years ago

I worked at a hedge fund at the start of my career, though it was somewhat atypical as it was a very new fund and had more of a startup environment than a well established hedge fund. The work was a fantastic split between analysis and building new software to run the fund.

But to your point, the CTO of the fund was a pure math phd who got into finance/coding when his advisors asked "Ok so now how are you going to make money". which is common for most of the heavy duty quants I know.

javaistheworst• 12 years ago

Not mentioned but important is coding - if you are a quant in an IB these days, you will be expected to do some level of coding - often C++, Python, and maybe some Excel VBA to plug things in for the desk to play with, while IT production-ise the rest intop the RMS and trading apps.

gadders• 12 years ago

while IT production-ise the rest intop the RMS and trading apps

Generally to software engineer it so it performs properly, can be put on a grid, etc etc.

mlrtime2• 12 years ago

"Hirers tend to be looking for strong programming and data management skills as much as mathematical ability"

This cannot be over emphasized. You cannot just have an aptitude for math/statistics/probability. You will need to be able to write high performance production quality code.

brador• 12 years ago

Bug free first time and write code fast also helps.

markovbling• 12 years ago

Spot on.

I got a job in finance as a quant and spent the first year building automated processes to pull portfolio holdings data from email attachments and scrape data from a bunch of different sources.

branchless3• 12 years ago

95% of quant code is not only fails to achieve low-latency, it's utterly incorrect, unmaintainable and frankly deranged.

Hansi4• 12 years ago

Agree mostly, even when wanting to deliver a perfect solution that's simply not an option because of requirements for speed of delievering results and lack of man power.

dreamweapon7• 12 years ago

So true. Of course, you better not tell that to the person who wrote it. You might not get your bonus.

ratsbane• 12 years ago

That might also be true for 95% of all code.

kasey_junk5• 12 years ago

Now admittedly this is sampling bias, but I have never seen code written by a quant that could be put into production without being reworked by a software professional.

The skill sets are in some way exclusive of each other. Quants do lots of exploratory work. This involves tons of one-of experiments and throwing away things that don't work. They often frequently don't have the operational understanding of the way the systems they interact operate. Further, making stuff fast on a computer is a very, very particular skill. People that could do all of that are extremely rare (such that I've never met one).

vasilipupkin• 12 years ago

Sampling bias. At least in HFT, the days of hiring quants who can't code are over.

chollida13• 12 years ago

Having hired a lot of quants and programmers in finance I can probably give a bit of background on what to expect:

Get this book, read it and understand it.

http://www.amazon.com/Heard-Street-Quantitative-Questions-In...

Quants tend to be in 1 of 3 categories:

1) pricing quants, you work for a bank or investment house like Goldamn. You know stochastic calculus very well, you know finite differencing like the back of your hand. You'll know every way to look at a derivative product. You can program in matlab. You create the next big thing like CDO's or CDS's

If you love math, this is where you want to be.

2) Quants who trade You work at a hedge fund. You can program in python with scikit or use R. You don't know calculus maybe as well as a pricing quant but you know some area of the market much much better. You know stats like its your mother tongue.

3) Risk quant/programmer. You do modelling all day for a trader or risk manager. You can take a portfolio and model any feature that someone ask for. Var, beta, greeks, you can spit them out quickly. You know C++, excel and R. You might have been an engineer in a former life.

This is often considered the low position in the quant hierarchy. This is how some programmers break into the industry.

4) I lied there is actually special category 4). This is the professors of quants. You sit around all day and think about the next big equation, or how to model derivatives better than black scholes. If you are one of these people chances are your name is known in the industry:)

EDIT someone asked if you can do these without a math degree. The short answer is probably not. YOu'll need a math, engineering, or physics degree, unless you really are driven to learn hte math yourself.

A comp sci degree might work but you would be the exception and you'd be fighting up hill. Ask your self honestly, how many branches of mathematics have you self taught yourself and you'll get your answer. For most the answer is none, for a select few the answer is yes.

Someone asked about brain teasers. They do get asked, you have to deal with it, whining in an interview that this type of question gives no useful hiring indicator won't get you hired. I don't ask them but they are common:(

We throw around brain teasers at work during the day trying to stump each other. I guess some of it is trying to look smart. Some of it is that we just really like to dissect any problem and figure it out.

I think the biggest reason for asking brain teasers is that at a hedge fund there are no rules for how to make money, excluding legal. They want people who can think outside the box. it turns out that its really tough to test for "can the candidate think outside the box"?

Trading is a higher stress job than most other math or programming jobs, what we are trying to see is not only are you smart, but can you think on your feet and not get stressed out, because if an interview stresses you out, whats going to happens when a $50,000,000 position that should be going up starts to go down.

Are you going to complain that the model says it should go up and the market isn't being fair, or are you going to accept what's happening and get back to work? You'd be surprised at the number of people who chose option 1.

I ask a bunch of questions that some people feel are brain teasers. In between questions I'l throw out what's the square root of 225 to see how the candidate reacts. Good traders seem to be exceptional at mental math, with very, very few exceptions.

I'll also ask alot of probability questions. Get ready to know what your expected payoff is if you gamble on dice games, its basically what you do every minute of the day when trading:)

Now if you are a programmer, how do you get into the industry? You need to know stats, machine learning, and programming, really well.

And I don't mean know machine learning, like "I tool an nlp library and stiched it together to do sentiment analysis on a corpus of text". I will ask what algorithms the underlying library used. You used SVM, great talk to me about your kernel selection methods. I want to know that you understand the math, and more importantly the assumptions and limitations of the library you are using.

The reason is that when you trade on a model that is based on your machine learning, I want to know that you know when it breaks. Finance is an industry that loves to model but has crashes that are predicted to happen 1 in 1000 year events happen every 10 years.

I love helping programmers who want to become quants get into the industry. Please feel free to ask if you have questions!

radikalus3• 12 years ago

Pay is reasonably divided based on those 4 category breakdowns as well.

1) High guaranteed, little upside 2) Low guaranteed, high upside 3) Moderate guaranteed, little upside, better QoL? 4) Low, none..., excellent QoL

I'm not sure how I'd feel discussing kernels of an SVM with someone -- to me, that feels pedantic. I generally feel that the fundamental driver to 'models no longer working' is evolving covariance dynamics (changing linkages) -- this has very little to the mechanisms of most ML tools.

Perhaps the metaphor I'm looking for is that I wouldn't expect a carpenter to be able to build and explain the components of a power drill to use it to help my house.

QuantFi is a huge discipline -- you build teams with hopefully a mixed bag of skills. On the trading side, I'd rather have someone with experience w.r.t to the market + products than math-jutsu any day.

Igglyboo• 12 years ago

How high is high and how low is low? I'd assume even the lowest payed quants are making high 5 or low 6 figures at a bank.

brotoss• 12 years ago

Can you do 2 or 3 without a CompSci/Math degree?

kasey_junk5• 12 years ago

Most quants do NOT have Comp Sci degrees. There is a lot of Math degrees in teh field but physics, signals processing, etc are also common.

Hansi4• 12 years ago

My team is a mix of 2 and 3, we have comp sci, math, actuarial, engineering and physics people with about an even split. Oh and one quant dev who was a medical doctor but found programming more fun. So it's all sorts.

Dalkanon• 12 years ago

How would one go about getting a job as a #3 with an MS in economics but no practical finance experience? I can code reasonably well, know stats reasonably well, and know calculus reasonably well, but could easily bone up on all 3 in about 2-3 months, enough so to confidently pass the interview process. But how would I get an interview without any finance connections?

kasey_junk5• 12 years ago

People act like finance is some secret inner sanctum, but it isn't. Finance companies/hedge funds advertise on job boards like any other company. They also often use very aggressive recruiters so finding the recruiting company du jour in your area and talking to them can help.

radikalus3• 12 years ago

Lots of options:

One-hops (1-2 year stint then transition out)

1. Programming gig at finance facing software shop 2. Programming gig at exchange

No-hops

1. Work on popular open source framework in heavy use (ZeroMQ, QuickFix, pandas, sympy, sklearn, etc) 2. Find headhunter/recruiting agency 3. Attend local finance oriented meetups and schmooze

I wouldn't trivialize the hiring process -- all of these roles are pretty competitive.

dreamweapon7• 12 years ago

Someone asked about brain teasers. They do get asked, you have to deal with it, whining in an interview that this type of question gives no useful hiring indicator won't get you hired.

Or to put it another way: if your hiring culture enshrines shallow, game-show style intellectualism along with such a condescending, "just suck it up" attitude towards candidates... then don't whine that you can't find decent programmers.

FLUX-YOU• 12 years ago

It's just a culture filter. If they have data backing up their methods, that would be nice to see and compare to Google's hiring process that rejected puzzles and brain teasers. I personally don't think there's any correlation with brain teasers and programming ability though.

michaelochurch2• 12 years ago

Now if you are a programmer, how do you get into the industry? You need to know stats, machine learning, and programming, really well.

My experience being a quant and being around quants is that, sadly, they don't get to use much machine learning. Some do, but it seems like 97-98% of the work is much more mundane.

Am I correct in perceiving that many hiring managers expect more in the way of interesting experience than they really need (or have to offer in the work that needs done)?

chollida13• 12 years ago

Am I correct in perceiving that many hiring managers expect more in the way of interesting experience than they really need (or have to offer in the work that needs done)?

Yes I think you are Michael. Especially for quant jobs 2 and 3 that I enumerated.

The only reason I listed machine learning is that it is the trogan horse that gets programmers to learning stats. I can't over emphasize enough just how much you need to know stats. half of trading is knowing stats as all good traders trade only when they have the advantage. 100% upside for 10% downside is a good rule of thumb.

I mentioned the deep dive into the machine learning techniques as unfortunately most of the programmers I meet who call themselves data scientists, just aren't very good at stats. I'll ask them what methods they use and they'll tell me the library they used.

Unfortunately most interviews go like this:

me: I see you did some K-means clustering, tell me about it.

them: Well, we used R to cluster related books into groups.

me: how did you choose the inital partition

them: blank stare, um the library does that.

me: yes, well I mean did you use Forgy or Random Partition

them: I don't know what those are. That's just random trivia that I would look up when working. Do you find asking random trivia helps you hire people:

me:...So do you have any questions for me?

Hedge funds have lots of mundane programming jobs. Most are back office stitching together WPF and accounting systems. Even at the HFT firms I've seen only a small portion of the programmers actually do anything on the main trading system.

I'd love to hear about your Jane Street experience here:)

Like most things the closer you are to the money the more you'll make and the more exciting your job will be:)

Most quant jobs that I've seen were very mundane, category 3 is most of the quant jobs. Though most will tell you that they are in category 1 :)

abrichr2• 12 years ago

This article and discussion are quite timely for me, as I was recently offered a position as a "quant analyst" at a derivatives arbitrage firm -- from what I understand, similar to 3).

My other two options are working at an ambitious new robotics startup, and a PhD in deep learning.

I have a few questions:

1) What would you say is a reasonable salary range for someone with a master's degree in computer engineering and a year of experience in back office, as well as an assortment of ML side projects? How high could you expect it to be in 2, 5, 10 years?

2) Is it very difficult to break into the industry? This opportunity just landed in my lap (recruiter), and I'd like to know how likely it is that I'll find something like it again.

3) Will a PhD in machine learning (and the resulting five year gap in the industry) make me more or less employable? How will it affect my salary/job opportunities?

4) Just how much of the job is reading and implementing machine learning papers, and how much of it is general software engineering?

5) Where can you derive meaning and satisfaction from a job in quantitative finance? How do you reconcile the opportunity cost to society from not working on directly socially beneficial applications in fields like medicine and artificial intelligence?

chollida13• 12 years ago

To be clear, I'm an engineering whose moved into the quantitative side, but am really poor at stochastic calculus, I haven't used it in 5 years. I wouldn't get a pricing job at a top their Investment house:) So I can't speak for the kind of quant job that most people consider to be the typical quant job.

Off the top of my head...

1) What would you say is a reasonable salary range for someone with a master's degree in computer engineering and a year of experience in back office, as well as an assortment of ML side projects? How high could you expect it to be in 2, 5, 10 years?

First off your education counts for nothing when negotiating salary. If you can do the job, you get the salary for the job. Some people really have a tough time of letting go of this. I don't care if you have Phd or are a high school drop out, you get paid based on performance and role.

In Toronto, starting $100,000 with raise to 200,000 at the high end in 10 years.

Bonus is 0 - 2x that, expect about 0.75 . Alot of that would be based on the firms record and not your own. It doesn't sound like you'd be actually making money so you have a chance to be higher if you develop trading strategies.

That's great money but not the kind of money some people think. You don't get huge bonuses until you, yourself, produce even larger profits.

2) Is it very difficult to break into the industry? This opportunity just landed in my lap (recruiter), and I'd like to know how likely it is that I'll find something like it again

Connections really help. A Phd really helps. Writing a piece of open source software that a firm uses really helps, Writing a paper that the firm uses really helps. Jobs can be hard to come by as the industry is pretty incestuous. People move around alot and that means someone trying to break in has to answer the question of why hire you instead of the guy whose done this for 10 years and I know everyone he's worked for.

3) Will a PhD in machine learning (and the resulting five year gap in the industry) make me more or less employable? How will it affect my salary/job opportunities?

If its for pricing, it probably won't help at all. If its a HFT then it helps.

Machine learning is used alot less than people think at most funds. Alot of people are under the assumption that you can just apply some machine learning to the market and make money, it just isn't possible for most people. There are just too many factors that can affect the price of a stock.

how do you model panic? Consumer confidence? Russia invading the Ukraine? OPEC selling oil below $80 a barrel? The US invading Iraq?

All of these affect the price of stocks, and its often modeled as an additional fudge parameter, that is positive or negative according to the whims of the modeler on that particular day, in other words, its a hack in the greatest sense:)

4) Just how much of the job is reading and implementing machine learning papers, and how much of it is general software engineering?

A lot less than you'd like. a ratio of 10:1 plumbing vs paper implementation is about what I do and I get to chose what i do:( If you think about it, the algorithm is small compared to the surrounding code you need just to get an order out the door.

Back testing can be 3 weeks out of 4 sometimes because for every idea you have that succeeds, you'll have 10 that fail at some level.

5) Where can you derive meaning and satisfaction from a job in quantitative finance? How do you reconcile the opportunity cost to society from not working on directly socially beneficial applications in fields like medicine and artificial intelligence?

Not touching this question with a 10 foot pole. I know I'm really excited for Monday mornings, others might not be.

dashboardfront• 12 years ago

5) Where can you derive meaning and satisfaction from a job in quantitative finance? How do you reconcile the opportunity cost to society from not working on directly socially beneficial applications in fields like medicine and artificial intelligence?

If this is a strong concern of yours you should probably go with one of the other two options. There's opportunities to make money in many industries. You might not end up with as high as a net worth as you would've if you went into quantitative finance, but that's not an absolute rule and you'll more likely burn out if you don't find satisfaction in your job. This isn't a dig towards anyone that is in the finance industry and enjoys their job, but it's common for people to end up quitting from dissatisfaction/work conditions.

Besides that, a robotics startup sounds pretty exciting.

gjm112• 12 years ago

How can you reconcile the opportunity cost to society [...]

There are two fine institutions that may help with this: taxation and charity. If you earn a lot of money, then you pay a lot of taxes and can afford to give a lot away.

Everyone likes to complain about taxation, but it's what turns a free market full of individuals and corporations all (to a good first approximation) trying to maximize their own wealth into something that benefits everyone.

And the most effective charities seem to be able to save a life (or provide a kinda-equivalent amount of other benefits) for something in the vicinity of $2000. (Important cautionary note: all such figures are very rough and you shouldn't trust them too much.)

So, suppose you have a choice between a quant-finance job of, let's suppose, exactly zero social value, and a job in medicine that pays $50k/year less. And suppose you'd be equally happy in either aside from ethical concerns. Then by taking the quant-finance job and giving away all your extra earnings, you give your government (let's say) an extra $20k/year to spend on schools and hospitals and police and roads -- and, unfortunately, various other things you might approve of less, so let's say it's the equivalent of $10k/year going to something obviously valuable like teaching, so you're paying for about 20% of an elementary-school teacher. And you give an extra $30k to (I hope) very effective charities, so maybe you are saving 10 lives a year.

So it comes down to the question: is the medical job more beneficial to the world than 20% of an elementary-school teacher and 10 poor Africans' lives per year?

You might answer that either way, but at any rate I don't think it's obvious that the answer is that the medical job is better.

(Some notes: I am not claiming that anyone who goes into finance in preference to another worse-paid job is obliged to give away all the extra money they earn. Only that doing so is one option, and that it might work out pretty well ethically speaking. It might be psychologically difficult to give away so much of one's earnings. It might be harder to "derive meaning and satisfaction" from things as indirect as tax and charity, compared with deriving them from one's actual work. It can be argued that quant-finance has positive social value, but I'd be skeptical of claims that it has much. I do not work in finance and never have, though being a mathematician it's always possible that one day I might.)

SkyMarshal• 12 years ago

Good traders seem to be exceptional at mental math, with very, very few exceptions.

I would have thought no exceptions. What are the characteristics of the few who make good traders despite not being exceptional at mental math?

auntienomen• 12 years ago

I know very successful quant traders who are so poor at mental arithmetic that they reflexively use ipython to compute 20% of $100M.

Writing correct trading algorithms has more to do with knowing what your blind spots are than being good at math party tricks.

airmondii• 12 years ago

It depends on the type of trader. Before the days of automation, it was essential. If you could do the mental math the fastest, you would get the best trades. Not surprisingly, this skill matters less when all your trading activity is conducted by algorithms.

tdees40• 12 years ago

Note also that pure derivatives quants like (1) are disappearing, and (3) is ascendant due to regulatory concerns (Dodd-Frank, et al).

pdovy• 12 years ago

This is a great rundown. It's worth mentioning though that if you are interested in HFT in particular but not necessarily being a "quant", there are lots and lots of really interesting technical problems to be solved as a pure software developer.

The upside is not the same as being a very successful trader, but it can still be head and shoulders above working at the Amazon/Google/Microsoft's of the world. Writing high performance, high availability trading infrastructure is hard, and scaling it globally is even harder. A successful HFT firm will be iterating on it's infrastructure fast enough that there is always interesting work to do, especially if you like distributed systems.

rev_bird• 12 years ago

someone asked if you can do these without a math degree. The short answer is probably not. YOu'll need a math, engineering, or physics degree, unless you really are driven to learn hte math yourself.

This is interesting, but I have a slightly different interpretation of the question: Assuming you _can_ learn the math yourself, will anybody believe you? Is the degree necessary, if only for pedigree purposes?

grayclhn4• 12 years ago

As far as getting an interview, I have no idea.

In a job interview for a position where the math is a requirement, it's going to be easy to convince people. There's very likely going to be someone who knows the math much better than you in the interview.

henrik_w• 12 years ago

Thanks, great information. I'm a software developer, and I have worked for a long time in the telecom/mobile/VoIP sector. Half a year ago I switched to SW development in the financial world (not quant though). I am currently halfway through a really excellent book aimed at technical people moving into finance (quant or otherwise). It's called The Complete Guide to Capital Markets for Quantitative Professionals" [0] (yes, I know, no prize for imaginative title).

So far, it's been a fantastic read. Detailed, good information, and very well written. I saw the recommendation for the "Heard on the Street" book. I was wondering if people can recommend some other books for moving into finance?

[0] http://www.amazon.com/Complete-Quantitative-Professionals-Mc...

fastball• 12 years ago

I'm in university for engineering right now, and this is an industry that I have been considering going into when I get out of school. What are things I can be learning/studying/reading/doing in the interim to give myself a head start?

I am already a good programmer and my mathematics ability is not lacking. My weakest point is probably finance, as I only have a rudimentary understanding of economics.

jskonhovd• 12 years ago

Do you have any advice for a back office developer trying to move into the front office? I am getting my master's part time from a good program in CS with specializations in Systems and Machine Learning. But, I am worried that my back office experience will get me stuck in those type of roles.

findjashua• 12 years ago

Thank you for writing such a clear and detailed post. I wish I had this information back in grad school.

I am very interested in #2 (quant trader). I studied Electrical Engineering back in school, and took classes on stats+probability as a part of my degree. I wanted to do something mathy, but through an interesting turn of events, I ended up in software development (Java -> Python -> Javascript).

I'm thinking of kicking the tires and refresh my stats/probability knowledge, but most online courses I could find are pretty introductory in nature. What would be a good path for me to be seriously considered for #2?

simplekoala• 12 years ago

Thanks for sharing your knowledge and helpful information!

danielkite• 12 years ago

One point to note. The more prestigious the school the more mathematics is thought in my experience. In my school the comp sci-major had more math lectures than the physics students (and better grades, as physics where becoming unpopular putting a higher bar on the comp. sci entry grades).

In my school you had a class for 6 months: introduction to programming, that's it! The rest of the 5 years where basically only math/algorithms (machine learning, statistics, probability, compiler algorithms and such).

I've heard that this is changing as the industry values practical programming experience, but boy would I've been pissed if I'd spent 5 years to learn ancient tech.

I'm quite pissed about people getting a comp. sci. degree from knowing some C++, HTML5 and bubble-sort nowadays from shabby universities. Get of my lawn!

rhodri• 12 years ago

I'd like to see an article titled "Why Get a Quant Job in Finance?"

kasey_junk5• 12 years ago

Because you get to work on really interesting math problems, in an environment that isn't stingy with pay or equipment and has clear objective measures of what things are important for the business?

abrichr2• 12 years ago

I think the question that rhodri poses is an important one. For me, satisfaction comes from more than just the solution to the immediate problem, or the amount of money I'm being paid to solve it. Satisfaction comes from knowing that what I'm spending my life on is meaningful in some greater sense.

Other ML fields like robotics and deep learning have virtually limitless applications that may benefit society in some way. Of course, I have heard the arguments for statistical arbitrage being useful by way of reducing inefficiencies in the market and providing liquidity, but this is far less tangible.

graycat7• 12 years ago

I got an applied math Ph.D. with a good course in measure theory and stochastic processes from a star student of E. Cinlar and a lot in optimization, wrote my dissertation on stochastic optimal control, had a solid background in software, especially in scientific computing, including a lot of applied statistics, sent a resume to Fisher Black at Goldman Sachs, and still have his nice answer back that he saw no opportunities for mathematics in finance.

Jerked the chains of lots of headhunters and got nowhere.

I concluded f'get about it.

Maybe since then it's changed.

rwmurrayVT• 12 years ago

When was this?

graycat7• 12 years ago

Long time ago, e.g., Fisher Black was still alive (maybe he's not now).

I hadn't yet heard of James Simons. The rumor I heard was that Simons liked to hire mathematical physicists from Russia.

I had no way to go to Wall Street and already know all about everything they they were doing. The martgingale convergence theorem, measurable selection, power spectral estimation, sure, all about Wall Street, no.

When I was in graduate school, people who understood both measure theory and martingales, Markov processes, etc. were like hen's teeth. Or, sure, essentially every pure math Ph.D. knows measure theory, but curiously, at least in the US, they rarely take a course in graduate probability. It's tough for me to believe that many physics students actually work at all carefully through measure theory. So, hen's teeth.

So, I thought that I had relatively good qualifications. And since I'd read E. Thorpe's book, Wall Street was one of my goals. But I couldn't get the time of day from Wall Street.

Finally, with the letter back from Fisher Black, I gave up. I mean, good grief, a lot of the interest is in the Brownian motion approach to the Dirichelet problem and Black-Scholes, and that was Fisher Black.

In a sense I can't fault Wall Street: A lot of people there are making a lot of money now, with, usually without, measure theory, etc., so clearly they don't need me.

Once again, over again, one more time, in the US the main way to make money is to own a business and make it valuable, not to work for someone else. So, I'm doing a start-up. Based on some mathematics, including measure theory? Yes. Having to do with Wall Street? No.

Right, LTCM: So, let's see, independent increments with the same distribution and not much more and satisfy the central limit theorem and, thus, get a Gaussian process, really, an approximation to Brownian motion. So, ..., and LTCM should have worked, right? Wrong! Those assumptions are only approximately correct, and moreover need some work on the rate of convergence to a Gaussian, with good attention to the tails, and, there, tilt. Boom. Someone kicks over a bucket of fish heads in Asia and ..., down goes LTCM.

deathflute3• 12 years ago

Hey, I wanted to send you a message but your profile has no email. Can you send me a message or put an email in your profile? Thanks.

graycat7• 12 years ago

How do I send you a message?

nether• 12 years ago

I'm filled with envy and rage over the fact I'm not good enough at math for this. I barely did above average in my grad level math courses in college (studied aerospace engineering). I worked my ass off; I should have breezed through it if I had the ability to be a quant.

mahyarm• 12 years ago

Math classes I've noticed just take more time because there is more detail to them, but if you keep up with the workload and go ask TAs questions at labs, it can be done. Out of all of my university courses, the math classes were the most workload heavy. They were 2x the workload of almost any CS class I took.

0800899g• 12 years ago

great quant info in here

poppow• 12 years ago

The whole industry is in recession. Those stuck in it just mental masterbate about crap, knowing that automation/ai will destroy their paradigm. In reality it's boring and nothing like the energy and passion in start ups/creative tech.

seongboii• 12 years ago

There's another way that hasn't really been mentioned yet, and that's to work for yourself via your own quantitative trading system or through Quantopian's crowdsourced hedge fund (https://www.quantopian.com/managers). Disclaimer: I'm an employee there

kofejnik• 12 years ago

commenting to bookmark (hope this is permissible here)

grayclhn4• 12 years ago

FYI: if you upvote the article, it will be listed under the "saved stories" link on your profile:

https://news.ycombinator.com/saved?id=kofejnik

(which I can't see, by the way)

sliverstorm2• 12 years ago

Upvoting also bookmarks, under "threads"

tacoman• 12 years ago

Darn. I thought this said "a Quaint Job in France" and I clicked on it. I was disappointed.

codeordie• 12 years ago

Ha - same thing happened to me!

How to Get a Quant Job in Finance

Related Stories