I work directly on this at the SEC and as such cannot comment on the matter publicly. I post here only due to the correlation between people who would read the comments of this post and those who might be interested in getting involved... because we are hiring.
Specifically, we're looking for 1-2 core devs (hacker/generalist types honestly). Python's our main language now & I'm trying to incorporate Haskell as well. Green card/Citizen required + NYC only (sorry, not up to me), salary 120k-190k/yr, 40hr/wk, awesome team run like a research arm.
Is financial regulation important to you? Do you think the SEC could do a better job at it? If so, consider this an invitation to come help out and make algorithmic regulation a reality.
I’m part of the SEC’s Quantitative Analytics Unit (QAU) – a small team of engineers and quants embedded within the SEC’s examination process. We have a dual mandate:
(1) Support the examinations of financial institutions (go to interviews, analyze data, etc…)
(2) Develop tools to for our team, and the SEC at large, to use. These tools can either be for making #1 more efficient or for expanding the reach and capacity of the SEC.
Our first tool to be deployed, the National Exam Analytics Tool, is already in production [1] but we are just getting started & we’ve yet to begin the most interesting challenges.
If you’re a great engineer (or great at machine learning, we are hiring both) that wants a place to grow while making an impact on the public good, I'd love to hear from you at martinow [at] sec [dot] gov.
Specifically, we're looking for 1-2 core devs (hacker/generalist types honestly). Python's our main language now & I'm trying to incorporate Haskell as well. Green card/Citizen required + NYC only (sorry, not up to me), salary 120k-190k/yr, 40hr/wk, awesome team run like a research arm.
martinow at SEC dot gov.