Dear all,I am interested in working in Quantitative Finance field.I have a PhD in Computer Science but I have not worked much with mathematics, so my mathematical skill is nothing special.Hence, I think that it could be difficult to apply for a Quant job which, in my opinion, requires advanced mathematical skill.What do you think?Also, I would like to know in case I apply for Quantitative Developer jobs, do I have a good chance?What skills will I need to prepare for this kind of job besides programming skill?Thank you very much.

You should be fine. Most Phd.'s from a decent program have pretty good knowledge of statistics and math. Also you do not need any special type of mathematical knowledge in most Quant Shops. Your Phd. counts for a lot more. Maybe you can fill in the gaps in your knowledge with something like CQF or self-study. If you are a really strong Computer Scientist, I respectfully recommend you consider other lines of work where your skills will be more respected ,Ex. Bay Area or a good Startup or a Software company specializing in leveraging Big Data such as Topsy, Datasift, GNIP. These companies require people with your background to perform massive scale NLP on Social Media Data. I don't know if you will make more or less money (I strongly feel that more or less you will be no better off either way) but you will be happier in my honest opinion. It is also possible that you are head over heels in love with Quant Finance, in which case ignore everything else I told you except that you have a strong chance with your background to become a Quant Developer or a Quant.

Tiamo, What was the topic of your PhD ?

Thanks capafan2 for your advice @DominicConnor: It was in information searching. Thank you.

As in Informational Retrieval ?I wonder if you've looked at data mining and text analysis ?

QuoteOriginally posted by: DominicConnorAs in Informational Retrieval ?I wonder if you've looked at data mining and text analysis ?Thanks DominicConnor. I have looked at these fields.However, I also would like to have your feedback on my chance to work in Quantitative Finance sector.Thanks everyone.

TiAmoIf I understand your maths knowledge, you frankly do not have a chance to get a quant or quant developer job. However you haven't given much description. for a quant developer job, you should have good maths skills - at engineering level - eg multivariable calculus/ linear algebra/statisticsas in dan stefanica's book stefanica bookso if you are comfortable with that level of maths skills you can definitely go for quant dev job for a quant job - you need graduate level maths/theoretical physics

No one can do a decent Phd. in Information Retrieval without going deep in Statistics - especially the Baeysian variety. His knowledge of a certain kind of math must be very strong. Not the part that uses Differential Equations or PDE's but the part that uses Stats and Machine Learning. Whether he would be accepted as a Quant totally depends on what kind of math they need. Besides most quants are just glorified quant devs anyways. Like all architects are just bloody good programmers. Just a caste system to make people be high and low.

++capafan2Most maths quants use most of the time is below graduate level. You just need to learn about Gaussian integrals and you'll blend right in.

OP asked whether he had a good chance of getting a quant job with average maths skills, not whether he could do the job.

It depends upon the role. For a hedge fund, you're likely to need to use your statistical knowledge (in particular econometrics/time series analysis). If you have a strong machine learning background this will be a distinct advantage. For a more "traditional" derivatives pricing quant in an IB, you will find it significantly harder to pass an interview. You would (likely) need more mathematical depth on the Partial Differential Equations (PDE)/stochastic calculus side, which can take some time to learn via self-study. If you're dead-set on that route, you could consider a Masters in Financial Engineering (MFE) course?

Depends on what you call quant developers. In derivative teams, there are many pure c++ developers in the quant team who dont know any more maths than the average CS grads. They maintain the library and frameworks while Quants build the models and pricers (PDE/MC). There are some people in between the two who might have grad level or higher maths but are primarily developers - they might get to work on forwards.CS PhD is very appropriate for 70-80% of quant developer jobs in derivative pricing area. Just dont tell them that you want to be a quant or they will ask you harder math questions in interviews. Revise your basic Calculus, Linear Algebra and Distribution Theory. Most of the maths asked during quant dev interviews are in the forms of puzzles.

QuoteOriginally posted by: ashkarDepends on what you call quant developers. In derivative teams, there are many pure c++ developers in the quant team who dont know any more maths than the average CS grads. They maintain the library and frameworks while Quants build the models and pricers (PDE/MC). There are some people in between the two who might have grad level or higher maths but are primarily developers - they might get to work on forwards.CS PhD is very appropriate for 70-80% of quant developer jobs in derivative pricing area. Just dont tell them that you want to be a quant or they will ask you harder math questions in interviews. Revise your basic Calculus, Linear Algebra and Distribution Theory. Most of the maths asked during quant dev interviews are in the forms of puzzles.It is interesting that you mention distribution theory (in the sense of generalised functions). I've not often heard that this is a requirement, as it tends to appear at the higher end of undergrad mathematics and less so in direct relation to quantitative work. Have you had different experiences?

Appologies, I should have said basic probability theory rather than distribution theory. I was referring to knowledge of various distributions and being able to use them to solve puzzles mainly. Ignorant as I am, I didnt know that 'distribution theory' referred to generalised functions.In this area, I was once asked some proofs on local vol (delta and heaviside functions). This was for an experienced quant dev position at a small place. They were really looking for what would otherwise be a quant position in big banks. They might be trying to get quants at a lower pay and call them quant dev.I have never been to proper quant interviews so I cant say for sure but I would imagine that some direct or indirect knowledge of generalised functions would be important for interviews. Someone else should confirm this...

QuoteOriginally posted by: ashkarAppologies, I should have said basic probability theory rather than distribution theory. I was referring to knowledge of various distributions and being able to use them to solve puzzles mainly. Ignorant as I am, I didnt know that 'distribution theory' referred to generalised functions.In this area, I was once asked some proofs on local vol (delta and heaviside functions). This was for an experienced quant dev position at a small place. They were really looking for what would otherwise be a quant position in big banks. They might be trying to get quants at a lower pay and call them quant dev.I have never been to proper quant interviews so I cant say for sure but I would imagine that some direct or indirect knowledge of generalised functions would be important for interviews. Someone else should confirm this...Actually amoungst more applied statistitions distribution theory wuold refer to exactly what you described.