I have an Msc in Physics. I got it after my CS Msc, because I got really hooked on physics after reading tons of Feynman stuff (FLoP, etc). I've been programmin

I have an Msc in Physics. I got it after my CS Msc, because I got really hooked on physics after reading tons of Feynman stuff (FLoP, etc). I've been programming since age 7 (C64), so I'm a programmer who got a Physics degree, not the other way around. I worked various SWE jobs initially, mostly C++. Then I started a Phd in Physics, but didn't finish, bc I did a startup [1]. The startup failed. Since then I've been working in various data/science roles at companies (Prezi, Facebook, now Fetchr). Data Science is a perfect fit for me (CS+Physics), there's nothing around it that I can't do, from setting up stuff on AWS, building dashboards, A/B testing, getting data out with SQL, doing ML with SKL or Pytorch, defining metrics and setting high-level company goals, explaining stuff to the CxOs. I'm really good at it, I have very high impact, get paid good money, make my own rules (mastery, autonomy, etc). Overall I got lucky because data/science exploded, and it just so happened that my interests/background/experience were a perfect fit. I got doubly lucky bc now Deep Learning is exploding [2], which is a perfect playground for people like me (play around with models, metrics, training, loss functions, etc.) I still buy lots of Physics books and sometimes read papers, but I'm trying to quit that, bc it's mostly pointless. [1] https://github.com/scalien/scaliendb https://github.com/scalien/scaliendb [2] https://news.ycombinator.com/item?id=19499515 https://news.ycombinator.com/item?id=19499515