EE Ph.D. seeks advice

[eephd]

Hi Everyone,

I have a Ph.D. in Electrical Engineering (signal processing) and 7 years experience in the aerospace industry (software development, system engineering, and production management). I'm looking to make a move into the quantitative finance field, including going back to school for an MFE. My graduate research heavily involved probability theory, random processes, etc. and I've kept my skills sharp over the last 7 years through work as well as by tutoring EE grad students.

Right now I'm trying to get an idea what to expect in terms of job prospects. What kind of salary / bonus should someone with my credentials expect? Would I start out at the same level as younger students, or would my compensation be commensurate with that of someone with 7 years experience? How necessary is the MFE? Would firms be willing to hire me without it?

Also, are there any other EE's out there, especially from the fields of signal processing, communications, information theory, or control? Would love to hear from you.

Thanks!

 

[DominiConnor]

You won't equate to a banking quant of 7 years.

You are most of the way to some interesting roles in algorithmic trading, which can be very lucrative.
Almost without exception all people with your sort of profile come in as newbies. Sometimes at the high end of newbie, but newbie anyway.

With all due respect you seem to know some very useful things, but they are components, not a product. Some bank or hedge fund will need to spend a bit of time letting you work out how to turn your skills into money.

It's not my job to sell you on quant finance, but to call it like it is, so the text above is probably not what you want to hear. So be it.

But...
The very highest compensation we observe for entry level people is for skill sets rather like yours. That may be $250K, or it may not. I don't know, and anyone who gives you a firm price is not being entirely straight with you. It could be any number up to that, or an abject failure to get an offer at all.

MFEs or a CQF is a tricky term in your context because you can either go as a straight quant, or make a play for algotrading where most of a MFE/CQF is simply not relevant.

You will need to learn some stuff of course, but I don't know you well enough to spot the holes.

 

[herron]

You won't equate to a banking quant of 7 years.

MFEs or a CQF is a tricky term in your context because you can either go as a straight quant, or make a play for algotrading where most of a MFE/CQF is simply not relevant.

I'm not sure that I understand this bit here. Does an MFE/MSCF not prepare you for algotrading? How do the two roles (straight quant and algotrader) differ? Thanks for the endless wisdom.

 

[echostate]

I'm not sure that I understand this bit here. Does an MFE/MSCF not prepare you for algotrading? How do the two roles (straight quant and algotrader) differ? Thanks for the endless wisdom.

my 2 cents before DominiConnor gives the correct answer ...

I guess straight quants mainly correspond to those working on derivatives in IB (sell-side quants), while algo.trading quants are those working on hedge funds (buy-side quants). The techiques used by them are different: the former focuses more on PDE/SDE and pricing models, while the latter concentrates on statistics/microstructure. Of course, there is no clear boundary between them.

MFE, without doubt, has the most effective curriculum for being quants -- this is why people pay their money. A typical MFE curriculum does cover basic techniques for algo. trading (or more generally, for being a buy-side quant), e.g., linear models, time series, stat. arb., portfolio manage. But the majority (60%--80%) of the courses in a typical MFE are designed for sell-side quants, since the demands of sell-side quants in the market is larger than that of buy-side quants (an IB can take dozens of quants, but a hedge fund usually can not). This is perhaps why DominiConnor said MFE is irrelevant to some algo. trading positions: because these positions may prefer some background in signal processing, statistical machine learning, data mining, etc, which are not intensively covered by MFE.

 

[josephamarks]

OMG, I just joined a firm that has quants as a software engineer, I have a PhD in Electrical Engineering, and experience in the areospace industry (among others).

Be honest at any interviews you have.

Leverage your mathematical, C++, and any SQL skills you have (excel is also helpful).

Learn as much as you can; .net skills for example are always valued!