You Think The Google Interview Is Tough? Try Getting A Job At A PE Firm(businessinsider.com)
businessinsider.com
You Think The Google Interview Is Tough? Try Getting A Job At A PE Firm
http://www.businessinsider.com/you-think-the-google-interview-is-tough-try-getting-a-job-at-a-pe-firm-2009-11
34 comments
I'm curious - have you interviewed at a financial company too?
I know for a fact that most public accounts of Google interviews are wrong. I have no reason to believe that public accounts of financial company interviews are right. I just assume that everything I read on the Internet is wrong until proven right. ;-)
FWIW, my Google interview was much harder than my two interviews with financial software startups. But I'm not certain if those startups are representative of the financial industry as a whole. Things might be different at Goldman, or hedge funds, or PE.
I know for a fact that most public accounts of Google interviews are wrong. I have no reason to believe that public accounts of financial company interviews are right. I just assume that everything I read on the Internet is wrong until proven right. ;-)
FWIW, my Google interview was much harder than my two interviews with financial software startups. But I'm not certain if those startups are representative of the financial industry as a whole. Things might be different at Goldman, or hedge funds, or PE.
I've interviewed with plenty of financial firms (large banks, asset management companies, smaller trading software firms, etc.) for engineer positions. The interviews are focused more on concurrency primitives, language features (knowing your tools), and database features (it's just too important in the financial world), with a bit of puzzles and basic computer science thrown in. It's not super hard, but it's also not a walk in the park. The questions are slightly different because of a different culture, but I can't say that it's radically different from a tech company interview, nor is it significantly easier.
Wait, you mean financial software positions. The linked article is about interviews for analysing firms or how to execute deals.
Yes, I mean financial software - I should have clarified it better. The discussion turned to a general "which interview is harder" question, so I thought I'd chime in. I have no idea what high powered analysis interviews are like - I don't know anything about this. I do know that I've met some incredibly smart analysts, so I can't imagine them being easy.
I would hope that engineering positions at financial companies require an interview process similar to that of Google's (although in practice my hunch is that they're not as strenuous, like you said), but my comment and the article aren't referring to engineering positions.
The simple truth is that people like the interviewee in the article just don't work on nearly as hard of problems as do Google engineers. Being an engineer myself, I've never had a finance job, but I've had plenty of friends and roommates who have. They need to know some math and have some Excel skills, but most of their time is spent on phone calls and Powerpoint decks. That's why even an easy first question in an interview for an engineering position (e.g. write a C function that reverses a string) is more difficult than the questions asked of these guys. Just look at the example of the most grueling question in the article. Describe the process of a leveraged buyout? That doesn't really require any analytical skills, creativity, or problem solving.
I really think it's suboptimal to have finance people running our businesses, Wall St., and our economy. In my experience, they have a hugely inflated sense of self-worth, which is based mostly on their hugely inflated salaries.
The simple truth is that people like the interviewee in the article just don't work on nearly as hard of problems as do Google engineers. Being an engineer myself, I've never had a finance job, but I've had plenty of friends and roommates who have. They need to know some math and have some Excel skills, but most of their time is spent on phone calls and Powerpoint decks. That's why even an easy first question in an interview for an engineering position (e.g. write a C function that reverses a string) is more difficult than the questions asked of these guys. Just look at the example of the most grueling question in the article. Describe the process of a leveraged buyout? That doesn't really require any analytical skills, creativity, or problem solving.
I really think it's suboptimal to have finance people running our businesses, Wall St., and our economy. In my experience, they have a hugely inflated sense of self-worth, which is based mostly on their hugely inflated salaries.
Heh. Writing a C function which reverses a string is something that sounds easy, but is actually very difficult to get right, depending on what the encoding is.
"I know for a fact that most public accounts of Google interviews are wrong."
Out of interest, how do you know this for a fact? I presume you were actually at most of these interviews?
Out of interest, how do you know this for a fact? I presume you were actually at most of these interviews?
Eh...I doubt you or I would understand the financial and legal considerations involved in taking a public company private. While I share your view about engineers not having enough power, you might want to consider that LBO deals and the like are basically 'financial engineering' and it's pretty technical...there's a lot more to it than the popular conception of 'take the CEO out for a round of golf, offer to double his pay if he recommends it to the shareholders, call up some rich people to throw in the capital and PROFIT'. The hardcore financial types I know work their asses off, have really good analytical skills, and know their calculus.
You do not need to know calculus to run a LBO model. Writing one is easy enough and most of the time the firm you are with has a few dozen variants that have been prebuilt for you. The analytical portion of PE isn't the hard part.
I think you're (drastically) under estimating the difficulty of passing a series of interviews at the tops banks or PE firms. For example, in many cases Goldman's have interviewed candidates more than 20 times before giving them a job. Recently someone I know got a summer internship as a trader at GS, on her interview panel there were 4 interviewers and each one was asking her questions in a different language (english, french, german and russian). Finance jobs or interview aren't easy.
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All this posturing about interviews is ridiculous. They are a very flawed tool at best. Whatever happened to actually learning what people were capable of?
The best hires are always the people that you've worked with in the past, or who come personally recommended.
Google's dick-swinging about its interviews is IMO not really one of their strong points. The interview process can eliminate some complete losers, but it probably also eliminates lots of people who would have been great on the job.
I have some empirical backing for this. During my brief tenure at Google our team worked with a lot of interns, and we made our recommendations for extending offers. Then, suddenly someone made a new rule that outgoing interns should be re-interviewed by members of a completely different team, I guess, for objectivity. And a lot of them were rejected through that process.
So we had people who had proved themselves in an initial interview, and during many months of on-the-job contributions, getting rejected because some wanker asked them some question about missionaries and cannibals or some other useless puzzle question.
And yeah, it was that sort of thing -- I remember one intern trooping dejectedly back into our offices and I and the tech lead tried to figure out what the hell the answers were to the question(s) they got asked. We couldn't figure out those puzzles either.
The best hires are always the people that you've worked with in the past, or who come personally recommended.
Google's dick-swinging about its interviews is IMO not really one of their strong points. The interview process can eliminate some complete losers, but it probably also eliminates lots of people who would have been great on the job.
I have some empirical backing for this. During my brief tenure at Google our team worked with a lot of interns, and we made our recommendations for extending offers. Then, suddenly someone made a new rule that outgoing interns should be re-interviewed by members of a completely different team, I guess, for objectivity. And a lot of them were rejected through that process.
So we had people who had proved themselves in an initial interview, and during many months of on-the-job contributions, getting rejected because some wanker asked them some question about missionaries and cannibals or some other useless puzzle question.
And yeah, it was that sort of thing -- I remember one intern trooping dejectedly back into our offices and I and the tech lead tried to figure out what the hell the answers were to the question(s) they got asked. We couldn't figure out those puzzles either.
Actually this is in no way surprising. I just graduated from school and let me tell you that the real brain drain is in our smartest students defecting to finance.
Why would someone with a 4.0 in a hard, rigorous subject go into engineering for a measly 60k a year starting salary + 20% raises when he can work in a finance industry where the top talent makes in the hundreds?
I had a lot of friends in the math department that were double business majors. I imagine that at least for quantitive finance positions, interviews such as these (if not way harder) are a must to separate the top talent from the elite talent.
Why would someone with a 4.0 in a hard, rigorous subject go into engineering for a measly 60k a year starting salary + 20% raises when he can work in a finance industry where the top talent makes in the hundreds?
I had a lot of friends in the math department that were double business majors. I imagine that at least for quantitive finance positions, interviews such as these (if not way harder) are a must to separate the top talent from the elite talent.
60k starting? That sounds low, even for 6 years ago when I graduated in CS. Google/Microsoft paid 80K starting for college grads back then -- have no doubt it is > 100K or more now.
I can confirm that Microsoft still started at 80K last year. I've heard Google is a bit higher, but still under a 100K.
A trader at a top tier firm, on the other hand, might have a $150K+ base first year out of school. Adding on bonuses, it isn't unusual for them to be making $1mil/year within 3-5 years (although the vast majority don't make it five years ...). A quant programmer (slightly less competitive/stressful) can expect to be making $200K/year+ within five years at a top tier quant firm.
It isn't really fair to compare programmers to bankers since the hours aren't really comparable. But the traders/quant-programmers I know (usually) only work about 60 hours a week.
All based on my relatively limited experience (~5 people/company - although I have no reason to suspect bias in my sample).
A trader at a top tier firm, on the other hand, might have a $150K+ base first year out of school. Adding on bonuses, it isn't unusual for them to be making $1mil/year within 3-5 years (although the vast majority don't make it five years ...). A quant programmer (slightly less competitive/stressful) can expect to be making $200K/year+ within five years at a top tier quant firm.
It isn't really fair to compare programmers to bankers since the hours aren't really comparable. But the traders/quant-programmers I know (usually) only work about 60 hours a week.
All based on my relatively limited experience (~5 people/company - although I have no reason to suspect bias in my sample).
Uh, I still do? The person writing the article seems to think that if you can approximate how many piano tuners there are in New York, you automagically get that Google dream job. They're both tough, but very different, processes. I can only hope the author doesn't work in the business side of software, as they clearly suffer from Shit's Easy Syndrome.
Ah, really? That's a Google question?
I'd love to hear what a good answer to that question is. Anyone up for it?
I'd love to hear what a good answer to that question is. Anyone up for it?
A good answer is something that gets you to the right order of magnitude that would be absolutely correct if your assumptions are correct. For example, the number of piano tuners in New York:
So there are eight million people in NYC. Let's say that each household is two people, on average. So four million households. Because NYC is crowded, not many people have pianos in their homes -- let's say one in fifty. So 80,000 pianos. Let's double that to account for the schools and concert halls, so 160,000 pianos. On average, let's say a piano is tuned once every other year. So each year, there are 80,000 tunings.
A piano has 88 strings, and let's say a trained tuner could tune about two per minute, so a piano takes forty-five minutes to tune. If the piano tuner knows where he's going, and makes appointments accordingly, let's say it takes another forty-five minutes to get from one appointment to the next. So ninety minutes is one piano tuning. One tuner works 50 weeks a year, 40 hours a week, so 2000 hours, or 1333 tunings. So 80,000 tunings / 1333 tunings per tuner = 60 tuners in NYC.
Of course, that assumes each tuner works full-time. If we assume there are part-time tuners, that number only goes up. I'd round to 100.
You see, the point isn't to get the exact number; the point is to show that you can figure out impossible problems.
So there are eight million people in NYC. Let's say that each household is two people, on average. So four million households. Because NYC is crowded, not many people have pianos in their homes -- let's say one in fifty. So 80,000 pianos. Let's double that to account for the schools and concert halls, so 160,000 pianos. On average, let's say a piano is tuned once every other year. So each year, there are 80,000 tunings.
A piano has 88 strings, and let's say a trained tuner could tune about two per minute, so a piano takes forty-five minutes to tune. If the piano tuner knows where he's going, and makes appointments accordingly, let's say it takes another forty-five minutes to get from one appointment to the next. So ninety minutes is one piano tuning. One tuner works 50 weeks a year, 40 hours a week, so 2000 hours, or 1333 tunings. So 80,000 tunings / 1333 tunings per tuner = 60 tuners in NYC.
Of course, that assumes each tuner works full-time. If we assume there are part-time tuners, that number only goes up. I'd round to 100.
You see, the point isn't to get the exact number; the point is to show that you can figure out impossible problems.
found this explanation from steve yegge:
http://steve-yegge.blogspot.com/2009_04_01_archive.html
"Shit's Easy Syndrome".
You know. As in, shit's easy. If it's easy to imagine, then it's easy to implement. Programming is just turning imagination into reality. You can churn through shit as fast as the conscious mind can envision it. Any programmer who can't keep up is an underperformer who needs to be "topgraded" to make room for incredible new college hires who can make it happen, no matter what "it" happens to be, even if they have to work 27 hours a day, which of course they can because by virtue of being new college hires, they have no social lives and no spouses or significant others, and they probably smoke a lot of crack from being in the dorms so they can stay awake for weeks at a time.
"Shit's Easy Syndrome".
You know. As in, shit's easy. If it's easy to imagine, then it's easy to implement. Programming is just turning imagination into reality. You can churn through shit as fast as the conscious mind can envision it. Any programmer who can't keep up is an underperformer who needs to be "topgraded" to make room for incredible new college hires who can make it happen, no matter what "it" happens to be, even if they have to work 27 hours a day, which of course they can because by virtue of being new college hires, they have no social lives and no spouses or significant others, and they probably smoke a lot of crack from being in the dorms so they can stay awake for weeks at a time.
Sorry for asking, but what's "Shit's Easy Syndrome"?
it's a term I lifted from steve yegge's [long-winded] software blog (RIP) - http://steve-yegge.blogspot.com/2009/04/have-you-ever-legali...
The short of it is when a Business man comes in and says "Can you build this facebook clone with integrations to our CRM, shits easy. See you in a week."
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I think people are over-estimating the difficulty because they're thinking about how difficult it would be for them to pass this interview.
The typical background for someone applying for this sort of job would have 5-10 years spent at a management consultancy firm, maybe a few years at an investment bank and an MBA. They'll have read thousands of business case studies and written dozens or hundreds themselves.
They'll have seen a number of LBO/IPO deals and will have spent hundreds of hours studying how these are structured.
These are the kind of people who when they read about a company automatically start thinking about market sizing and modelling.
Not being able to do a case study in an interview would be like a programming interviewee not being able to solve a trivial problem like FizzBuzz.
And as for the timing, it's just testing something that anyone with the appropriate background should be able to breeze through. If you're meeting with a C-Level client, running over your allocated time is incredibly rude, if you can't manage your time in an interactive discussion situation then you don't belong in the industry.
The whole article just sounds like it's based on the rants of a candidate who wasn't capable of doing the job they were applying for.
The typical background for someone applying for this sort of job would have 5-10 years spent at a management consultancy firm, maybe a few years at an investment bank and an MBA. They'll have read thousands of business case studies and written dozens or hundreds themselves.
They'll have seen a number of LBO/IPO deals and will have spent hundreds of hours studying how these are structured.
These are the kind of people who when they read about a company automatically start thinking about market sizing and modelling.
Not being able to do a case study in an interview would be like a programming interviewee not being able to solve a trivial problem like FizzBuzz.
And as for the timing, it's just testing something that anyone with the appropriate background should be able to breeze through. If you're meeting with a C-Level client, running over your allocated time is incredibly rude, if you can't manage your time in an interactive discussion situation then you don't belong in the industry.
The whole article just sounds like it's based on the rants of a candidate who wasn't capable of doing the job they were applying for.
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This sounds a lot like how my PhD oral qualifying exams went. Except I got 30 minutes of highly technical questions from all 6 committee members and then sat outside for 40 minutes while they deliberated if they should let me stay in graduate school (they did). After that I got to have two more personal interviews with more in-depth questioning. The whole ordeal lasted somewhere around 5 or 6 hours.
Dunno about PE firms, but the Google engineering interview was roughly comparable to my interview at Morgan Stanley. (The second was slightly rougher; one of the interviewers printed out the code they were currently debugging and asked me to find the bug.)
I wouldn't think you would need to be that selective in private equity. How hard is it to buy a healthy company with borrowed money, run that company into the ground, and then flip it a few years later?
I must admit, with the world fiat economy slowly eating itself alive, too big to fail, massive TARP bailouts left right and center, entire middle eastern fiefdoms just saying "Hey sorry about that 60 billion IOU but we're going to have to put an indefinite hold on it".
Financial professionals whining about how much it takes to make the wheel turn in their industry strike me as about as honest and reality based as dressage shops for unicorns trying to make a case for why their particular brand of mastery ought to sit at the top of human endeavour.
Financial professionals whining about how much it takes to make the wheel turn in their industry strike me as about as honest and reality based as dressage shops for unicorns trying to make a case for why their particular brand of mastery ought to sit at the top of human endeavour.
I've never been a fan of this kind of blind arrogance in the finance industry. I hoped the recession would at least have some effect on that, but it probably won't. Engineers don't have nearly enough power in this society.