Career advice for current MFE student with work-exp

[VaibhavChauhan]

Coming back to Quantnet after long time since I got admission in MFE

I am a current student of Financial Engg. in Univ. of Michigan. I am exploring the current requirements of the industry and the right skill set they are looking out. This market is very dynamic so wanna stay connected with latest updates.
Please let me know what should be my course of action for next 6 months before I start looking out for job.

Just to brief about me:
Final year student of Financial Engg. in Univ. of Michigan
Work-exp: 4-5 years in Hard core programming (in Java/J2EE). Have really very good programming skills in OOPs/Data structures/Design patterns etc. (Know C++ but not much coding experience)

I am looking for a role in finance industry and am open for various roles e.g. risk,quant,fixed income,trading etc.

Few queries:

A.) Considering my profile, kindly suggest the preferred order of following subjects as per industry demand:
1. Probability
2. Statistics in Finance
3. Programming/Data structures
4. Stochastic calculus/Discrete processes
5. Numerical methods

(Note: Please suggest in a very practical way as per actual industry demand, not from academic point of view)

This can be useful for any current student or professional.

B.) Is it that I need to develop very good skills in C++ as well, given I already have Java skills. I mean to say, is C++ preferred over Java to great extent? A few months back, got some idea that Java and C# is picking pace in latest quant world. Is it right?

C.) Is Professional Risk Management certification really useful for MFE students?

Andy, your comments are especially welcome.

Thanks guys.

 

[Ken Abbott]

FRM / PRM are useful AFTER you get a job. No one in industry will be impressed that you know how to take a test.

 

[VaibhavChauhan]

Thanks Ken. That makes absolute sense. However, I was thinking of PRM not just for a certificate to show, but was wondering if I can really learn something from it that Quant world looks for.

 

[Ken Abbott]

The math you learn won't be much different from what you know. The good thing about these certificates is that they provide guided reading for the motivated. And by motivated I mean people who will understand WHY it's important to learn the material. These programs provide the institutional background necessary to put everything into context. For example: Vasicek SF Monte Carlo. Why? IDRC for Basel 2.5. Eigensystem decomposition. Why? Efficient simulation. Jarque-Bera. Why? Regularity of non-normal data. ARIMA. Why? Financial time series have a peculiar sort of memory.

 

[VaibhavChauhan]

Ken, that was really good insight. I got your point reg PRM.