things are definitely changing in the post-2008 world. Much of what I wrote is colored by my own experience at Goldman 1998-2008. I must say that even today, on the Goldman/Morgan trading desks, people do wear multiple hats and junior traders still get coffee. And the talented ones still ramp up to $1M+ pretty quickly.
Hard to get any stats on this, but it would be indeed interesting to see. In the valley, there are also quite a few 9-digit exits with 2-digit equity percentages. My gut is that in today's scenario, the Silicon valley count would be higher.
Yes - the personality element is indeed very important. Wall Street definitely requires a thicker skin. But then Silicon valley cushions people too much.
Here's a popular interview 'puzzle' that is actually quite relevant to quant finance, i.e., backward induction. It can be viewed as a hybrid between categories 2) and 3).
http://www.techinterview.org/post/491500090/world-series
The blog post is for startup founders who are making very early-stage decisions on technology, hiring, funding etc. If you are not one of those, it's probably not very useful to you. We did receive appreciatory comments from people. I'm not sure why you say "wasting everyone's time" ...
Are you suggesting that we should go with Lift/Play instead of Django? If so, can you elaborate on your argument? As you can tell from the article, I'd love to see Scala beat Python, but I can't see Scala scoring over Python on the web framework front.
The good hedge funds are doing extremely well with algos. Graduating students from CS/Math/Stats have a great career here, not to mention the opportunity to do some really interesting work and make a lot of money.
Thanks for your support. Like I mentioned, I will circle back to Haskell as the business develops. If I was the only programmer in my startup, I would likely go with Haskell for important components of our software. But I have concerns about hiring a large team that would thrive in Haskell. One never knows - I'm keeping an open mind :)
Indeed! At the early stages of a startup, most decisions (including technical ones) have a strong emotional/instinctive flavor. When I worked at large corporations, the decisions were almost always devoid of emotions.
Thanks! Great articles. We are not compute-bound for the near-term, so it's not our most important consideration. As the business evolves, we will embark on a fresh language war where compute performance is likely to be a key factor.
A few more considerations will be posted in Part 2 of the post.
I appreciate your pointers - as the business grows and takes shape, a fresh evaluation will be required where some of the considerations you mention will be taken into account.