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Types of quant job which are available? (Ad's I have seen do not seem to fit what I've read here)

Well, I suppose it's nice to be able to pay for a family vacation out of pocket and not spare a second thought about it =).

Anyway, in terms of "glamorous" quant jobs...I have a serious question for everyone on the boards here:

Why exactly are you all just focused on the financial quant jobs? I believe James Simons put it best: "...At Goldman, these scientific types are called quants--some of you may have heard of quants. But at Google, they're just called employees--because they're all quants."

In fact, considering my last three [in person] interviews have been at startups (2 in Cambridge, one in NYC), this is question I constantly have to field over and over. "Why the switch from finance to technology?"

In reality, I see the roles as identical in what I like to do (the statistics, the munching on data, the pattern-finding, the nerdy-nerdy stuff). I'm analyzing data sets of various sizes (usually large) in order to try and piece together some sort of hazy patterns on which, after making enough diversified bets, I can eke out an edge, be it in online advertising (Cambridge cos), venture capital (NYC), or finance (waiting for a couple of Chicago contacts to formalize opportunities). As for "the markets" vs. "high-tech start-ups", the way I see it is that my work would be strikingly similar anywhere I go because I have a certain skill set that is good at certain things, which are applicable in very similar ways in both cases. So I'm not complaining about not dealing with trading/securities at a startup interview, or how our innovation affects the rest of the laypeople at prop trading firms.

Really, I would highly, highly recommend anybody with an MFE to look to Silicon Valley as well--simply because the skill set for data analytics roles draw from what I'd say are identical skill sets that quants need (at least on the statistical end--I doubt you'd need to do PDEs to price impressions).
 
Well, I suppose it's nice to be able to pay for a family vacation out of pocket and not spare a second thought about it =).

Anyway, in terms of "glamorous" quant jobs...I have a serious question for everyone on the boards here:

Why exactly are you all just focused on the financial quant jobs? I believe James Simons put it best: "...At Goldman, these scientific types are called quants--some of you may have heard of quants. But at Google, they're just called employees--because they're all quants."

In fact, considering my last three [in person] interviews have been at startups (2 in Cambridge, one in NYC), this is question I constantly have to field over and over. "Why the switch from finance to technology?"

In reality, I see the roles as identical in what I like to do (the statistics, the munching on data, the pattern-finding, the nerdy-nerdy stuff). I'm analyzing data sets of various sizes (usually large) in order to try and piece together some sort of hazy patterns on which, after making enough diversified bets, I can eke out an edge, be it in online advertising (Cambridge cos), venture capital (NYC), or finance (waiting for a couple of Chicago contacts to formalize opportunities). As for "the markets" vs. "high-tech start-ups", the way I see it is that my work would be strikingly similar anywhere I go because I have a certain skill set that is good at certain things, which are applicable in very similar ways in both cases. So I'm not complaining about not dealing with trading/securities at a startup interview, or how our innovation affects the rest of the laypeople at prop trading firms.

Really, I would highly, highly recommend anybody with an MFE to look to Silicon Valley as well--simply because the skill set for data analytics roles draw from what I'd say are identical skill sets that quants need (at least on the statistical end--I doubt you'd need to do PDEs to price impressions).

Good point.
 
Actually as a headhunter, and mentioning no names I will share that there exist quite a few people with the job title of Quantitative Analyst at Google.
But it is a good question.

A job can be measured as a series of discounted cash flows, indeed I've been engaged by a bit of the UK government to do just that.

Google has done very well for itself, but if you are going to be paid with a good chunk in share options you have to believe that success will continue. That means you actually don't care how big G is today, but how much it will grow in the next 5-10 years.

Anyone care to predict that ?

Also there is a good number of skills that are not in any way portable, think of this as liquidity risk. Some stuff at G only happens at G or at least on G does it that way. That applies to banks of course. I worked for the last Discount House a rather specialist type of banking, when they were shut down, things were awkward. Same with technical skills, JP Morgan relies heavily on SmallTalk 80 (as in 1980), and if you read as many resumes as I do you see some skills that have very narrow bases.

There is value to "banking" experience that does not really translate when you talk about firms that are mostly technology like Google or Microsoft. Yes they do some good tech, but whole working products require some outstandingly dull narrow work, testing, network operations, backups. So do banks.
 
Google has quantitative analysts. Those require PhDs. Aka they look for the same people that RenTec does. I once passed two phone interviews for their decision support engineering analyst, had an invitation to interview onsite at Mountain View, then literally got that canceled due to a "lack of fit" and missed 2Q earnings, and since then, I've tried to restart the process, but that same recruiter wouldn't give me the time of day due to a "recent" application.

So every time I use Google nowadays, especially in pertinence to my job hunt, there's a slightly bitter aftertaste in my mouth knowing that two very smart Googlers (including one with like 30 years of post-Stanford statistics PhD silicon valley experience) gave me the green flag. Another Google guru, Don Dodge, told me to keep pressing since my background is fantastic and eventually I'll reach high places.

Which, not to count my chickens before they hatch, may be happening sooner than later. But yeah...the world revolves around data. Those who can make sense of the extensive amount of it will be in demand. Whether in finance, technology, bioinformatics, etc. etc. etc...

Sometimes I wonder whether or not a statistics PhD just to see so many of the things I've only heard about (regression trees, random forests, vector machines, neural nets, machine learning...argh argh argh wish I knew it more) since I'd probably love all of the applied stuff (and would utterly despise the proofs).
 
We don't recruit for Google, indeed until Ilya wrote this I had been under the impression that they didn't use external recruiters at all.
But it seems that they don't handle the process element of recruitment better than the average bank.
 
Google has quantitative analysts. Those require PhDs. Aka they look for the same people that RenTec does. I once passed two phone interviews for their decision support engineering analyst, had an invitation to interview onsite at Mountain View, then literally got that canceled due to a "lack of fit" and missed 2Q earnings, and since then, I've tried to restart the process, but that same recruiter wouldn't give me the time of day due to a "recent" application.

So every time I use Google nowadays, especially in pertinence to my job hunt, there's a slightly bitter aftertaste in my mouth knowing that two very smart Googlers (including one with like 30 years of post-Stanford statistics PhD silicon valley experience) gave me the green flag. Another Google guru, Don Dodge, told me to keep pressing since my background is fantastic and eventually I'll reach high places.

Which, not to count my chickens before they hatch, may be happening sooner than later. But yeah...the world revolves around data. Those who can make sense of the extensive amount of it will be in demand. Whether in finance, technology, bioinformatics, etc. etc. etc...

Sometimes I wonder whether or not a statistics PhD just to see so many of the things I've only heard about (regression trees, random forests, vector machines, neural nets, machine learning...argh argh argh wish I knew it more) since I'd probably love all of the applied stuff (and would utterly despise the proofs).

I think I should consider a change of career. I've literally figured out what's wrong with you - have you ever taken a narcissistic personally test?
 
We don't recruit for Google, indeed until Ilya wrote this I had been under the impression that they didn't use external recruiters at all.
But it seems that they don't handle the process element of recruitment better than the average bank.

Oh they don't use outside recruiters. Just that their internal ones can't even give a candidate the time of day. I wish they did use external recruiters. That way, I could actually get one to speak with me.
 
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