I often ask myself, do quants need to know all traps and dirty tricks solving multi-factor PDEs numerically or with asymptotic math approaches, solving inverse problems, like model calibration, exploiting, say, CUDA over the grid optimally?
Isn't their strength: financial engineering, structuring, model validation, risk and product controlling methodologies? Isn't a quant's challenge to provide rationales for decisions and accelerate time to insight?
Quants in their high-level work enjoy UnRisk-Q's bank-proof pricing and calibration engines, computing blazingly fast programmatically manipulated from a declarative financial and mathematical programming environment empowering quants to build what they think in a style they would describe the problem.
See: Documentation Center
Click on deal types, VaR, parallelization, ... and look for examples.
