- Joined
- 1/18/20
- Messages
- 93
- Points
- 18
Hello all,
I would like to get advice from people inside the world of Quantitative Finance about what chances are there nowadays of getting in as a Quant Developer without much knowledge of Financial Mathematics.
I hold a PhD in Computational Mechanics from a mid-upper tie University here in the UK (Russell Group), so I have experience in numerical methods (finite differences, finite elements, more exotic numerical methods, numeric codes for solving PDEs), and coding numerical algorithms in the object-oriented paradigm, C++98 mainly, and in the procedural one, Matlab and Fortran.
My background is in Mechanical Engineering, and I am by now in my thirties.
Since I got my PhD and cut my further ties with the University this past June, I set out to fill my knowledge gaps eyeing for a role in Quantitative Finance.
I feel my weak spots are mainly in the field of Probability&Statistics (building a base towards Machine Learning eventually), Software Design and Patterns (never read gang of four C++ book) and obviously Financial Engineering itself.
I set out to improve my knowledge on these topics, aiding myself with books, MOOCs and online university lectures, but have since realised that books like Joshi's 'Concepts and practices of math finance', his other C++ book, Hull's book on Options and Derivatives, Statistics textbooks and the likes take a good two or three months of study each, to get a good understanding out of them, and a reasonable number of exercises done.
Even having completed that, I would need further time to go through the interview preparation books like 'Cracking the Coding Interview' and then Stefanica's or Joshi's more quant-focussed interview books.
By now, this period of many months of self-studying has led to much self-doubt because I am quite on my own in doing this, and not in any way involved with the finance world. In this regard, signing up to a MFE degree would have helped.
Keeping my current self-study pace, I believe I may be ready for interviews perhaps in June or for the summer.
Since I am studying for this since this summer, by then I would have spent 1 year or so preparing, which is basically the same period spent enrolled in a MFE (minus the enrollment fee that I do not think I can afford, as right now I have kept afloat through my savings and a 0-hours contract at a menial job).
All in all, you could say my profile fits that of an aspiring Quant of 10-15 years ago.
What do you think my chances are, coming interview time? Should I angle for classic price or risk roles at banks or algorithmic trading, given my background in low level programming languages?
And also, does the classic Quant Developer figure ("glorified programmer" they say) still exists o has it been fully or in part superseded by Machine Learning automated trading?
Thank you for taking the time to read this,
and Cheerio!
I would like to get advice from people inside the world of Quantitative Finance about what chances are there nowadays of getting in as a Quant Developer without much knowledge of Financial Mathematics.
I hold a PhD in Computational Mechanics from a mid-upper tie University here in the UK (Russell Group), so I have experience in numerical methods (finite differences, finite elements, more exotic numerical methods, numeric codes for solving PDEs), and coding numerical algorithms in the object-oriented paradigm, C++98 mainly, and in the procedural one, Matlab and Fortran.
My background is in Mechanical Engineering, and I am by now in my thirties.
Since I got my PhD and cut my further ties with the University this past June, I set out to fill my knowledge gaps eyeing for a role in Quantitative Finance.
I feel my weak spots are mainly in the field of Probability&Statistics (building a base towards Machine Learning eventually), Software Design and Patterns (never read gang of four C++ book) and obviously Financial Engineering itself.
I set out to improve my knowledge on these topics, aiding myself with books, MOOCs and online university lectures, but have since realised that books like Joshi's 'Concepts and practices of math finance', his other C++ book, Hull's book on Options and Derivatives, Statistics textbooks and the likes take a good two or three months of study each, to get a good understanding out of them, and a reasonable number of exercises done.
Even having completed that, I would need further time to go through the interview preparation books like 'Cracking the Coding Interview' and then Stefanica's or Joshi's more quant-focussed interview books.
By now, this period of many months of self-studying has led to much self-doubt because I am quite on my own in doing this, and not in any way involved with the finance world. In this regard, signing up to a MFE degree would have helped.
Keeping my current self-study pace, I believe I may be ready for interviews perhaps in June or for the summer.
Since I am studying for this since this summer, by then I would have spent 1 year or so preparing, which is basically the same period spent enrolled in a MFE (minus the enrollment fee that I do not think I can afford, as right now I have kept afloat through my savings and a 0-hours contract at a menial job).
All in all, you could say my profile fits that of an aspiring Quant of 10-15 years ago.
What do you think my chances are, coming interview time? Should I angle for classic price or risk roles at banks or algorithmic trading, given my background in low level programming languages?
And also, does the classic Quant Developer figure ("glorified programmer" they say) still exists o has it been fully or in part superseded by Machine Learning automated trading?
Thank you for taking the time to read this,
and Cheerio!