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Escher
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Where do I go from here?

February 4th, 2016, 6:28 pm

I'm fairly happy in my current job, but I often get a nagging feeling that I don't really know what else is out there, and I might be missing out on something better.I've got a PhD in machine learning, and I've been working as a quant researcher in a small systematic hedge fund in London for a couple of years. Although it's a small shop, there are alumni from some big names there, so I've been able to learn quite a lot from them. I feel like I'm getting to the point where I could hold my own in an interview for a more senior position.Current total comp is about £100k in a good year. Given that the effective marginal tax rate on £100 - 120k is over 60%, I'm not sure I'd consider moving to a different firm unless I got a decent bump. Any suggestions about where I could go from here? I think I'd be happy to consider most jobs (e.g. HFT, Ibanking) as long as the work is interesting. Though I recognise that one man's 'interesting' is another man's mind-numbing drudgery.In any event, suggestions are welcome. Especially the sarcastic ones where you tell me to go and work as a farm hand.
 
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mbunea
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February 5th, 2016, 7:29 am

Taxi drivers earn a lot in tips. Free tip: not all taxidrivers, the nightshift ones.
 
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Escher
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Where do I go from here?

February 5th, 2016, 10:46 am

QuoteOriginally posted by: mbuneaTaxi drivers earn a lot in tips. Free tip: not all taxidrivers, the nightshift ones.Not a bad idea if it weren't for the competition from uber. Also not sure I could muster the requisite casual racism.
Last edited by Escher on February 4th, 2016, 11:00 pm, edited 1 time in total.
 
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Cuchulainn
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February 5th, 2016, 1:51 pm

QuoteI've got a PhD in machine learning,Very popular/trendy at the moment. What is the expected lifetime of this somewhat (IMO) niche skill? Are you wiling to retrain?
Last edited by Cuchulainn on February 4th, 2016, 11:00 pm, edited 1 time in total.
 
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Escher
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Where do I go from here?

February 5th, 2016, 6:10 pm

While machine learning is currently fashionable, I agree it's niche, and the applications to finance are limited. But I haven't really been using those skills directly in my role as a quant, any more than a fluid-dynamicist turned quant would use their research. My job is more about critical thought, skepticism, and attention to small details.I do have a masters in quant finance too, though.
Last edited by Escher on February 4th, 2016, 11:00 pm, edited 1 time in total.
 
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katastrofa
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February 5th, 2016, 6:18 pm

Could it be that your perception of English taxi drivers have something to do with the fact that you're being underpaid?
 
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Escher
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Where do I go from here?

February 5th, 2016, 6:55 pm

QuoteOriginally posted by: katastrofaCould it be that your perception of English taxi drivers have something to do with the fact that you're being underpaid?Mind elaborating on that?
 
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Cuchulainn
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February 5th, 2016, 7:33 pm

(double)
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Cuchulainn
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February 5th, 2016, 7:35 pm

QuoteOriginally posted by: EscherWhile machine learning is currently fashionable, I agree it's niche, and the applications to finance are limited. But I haven't really been using those skills directly in my role as a quant, any more than a fluid-dynamicist turned quant would use their research. My job is more about critical thought, skepticism, and attention to small details.I do have a masters in quant finance too, though.In general, a given technology has a 1/2 life of 8 years (except C++).Strange, but I still the do same maths I did in 1974. Never thought I would ever see Crank Nicolson again. All the other stuff I learned has been superceded. One day C++ will not be used either.I have no idea where good jobs are in research. I think they are all in China. You can't separate research and manufacturing.Lots of jobs in programming.
Last edited by Cuchulainn on February 4th, 2016, 11:00 pm, edited 1 time in total.
 
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Cuchulainn
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February 6th, 2016, 6:30 pm

An off-topic question, maybe: how can you make pure maths (topology in all its form, measure theory, category theory) into something that is remotely computational? The only nice example I know is homotopy that can be used to solve nonlinear equations.Did lots of measure theory but the only useful example I could relate to is Radon-Nikodym. Why do MFE students without maths background have to learn all those sigma algebras? I think it's because the space is uncountable. Try approximating a sigma measure by a series or FEM.just curious
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Gamal
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February 6th, 2016, 7:43 pm

QuoteOriginally posted by: CuchulainnWhy do MFE students without maths background have to learn all those sigma algebras?To learn what they really are, forget and never bother again.Every finance papers starts with "Let (Ω,Σ,P) be a probability space" and that makes me crazy.
 
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Cuchulainn
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February 6th, 2016, 8:31 pm

QuoteOriginally posted by: GamalQuoteOriginally posted by: CuchulainnWhy do MFE students without maths background have to learn all those sigma algebras?To learn what they really are, forget and never bother again.Every finance papers starts with "Let (Ω,Σ,P) be a probability space" and that makes me crazy.Indeed. I did stumble on this thesis from a Dutch guy in Eindhoven (home of Philips semiconductors). I would reckon these practical guys want to apply it!here?
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bearish
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February 6th, 2016, 9:31 pm

QuoteOriginally posted by: GamalQuoteOriginally posted by: CuchulainnWhy do MFE students without maths background have to learn all those sigma algebras?To learn what they really are, forget and never bother again.Every finance papers starts with "Let (Ω,Σ,P) be a probability space" and that makes me crazy.First, this is clearly another case where we can blame the French! I don't know the local scene well enough to decide whether it's really people from Paris or Strasbourg, but probably both. Second, that being said, the concept of a filtration is actually rather useful when you want to be somewhat precise about concepts like conditional expectation, Markov process, martingale, stopping time, admissible trading strategy, to mention a few. Nothing is terribly complicated about this stuff in discrete time, finite state models, but all hell breaks loose when you go to continuous time and state models, and I agree that your typical MFE student is wholly unprepared to deal with that. In teaching such people I generally resort to being a bit formal about the concepts in simple models (typically the binomial) and arguing by analogy in the limiting continuous case.
 
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Gamal
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February 6th, 2016, 10:06 pm

QuoteOriginally posted by: bearishFirst, this is clearly another case where we can blame the French! The opposite. If you've got a good French education, you don't feel a need to show yourself as an expert in sigma fields, you just deal with stuff which is useful.QuoteOriginally posted by: bearishSecond, that being said, the concept of a filtration is actually rather useful when you want to be somewhat precise about concepts like conditional expectation, Markov process, martingale, stopping time, admissible trading strategy, to mention a few. Everhing was done some 50 years ago. Why repeat in a finance paper?
 
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Escher
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February 7th, 2016, 9:12 am

QuoteOriginally posted by: CuchulainnAn off-topic question, maybe: how can you make pure maths (topology in all its form, measure theory, category theory) into something that is remotely computational?Off the top of my head, the ideas around persistent homology, and application of geometrical ideas to MCMC.But it's an open question as to whether you can do anything genuinely novel or useful with either of them.