This article and discussion are quite timely for me, as I was recently offered a position as a "quant analyst" at a derivatives arbitrage firm -- from what I understand, similar to 3).
My other two options are working at an ambitious new robotics startup, and a PhD in deep learning.
I have a few questions:
1) What would you say is a reasonable salary range for someone with a master's degree in computer engineering and a year of experience in back office, as well as an assortment of ML side projects? How high could you expect it to be in 2, 5, 10 years?
2) Is it very difficult to break into the industry? This opportunity just landed in my lap (recruiter), and I'd like to know how likely it is that I'll find something like it again.
3) Will a PhD in machine learning (and the resulting five year gap in the industry) make me more or less employable? How will it affect my salary/job opportunities?
4) Just how much of the job is reading and implementing machine learning papers, and how much of it is general software engineering?
5) Where can you derive meaning and satisfaction from a job in quantitative finance? How do you reconcile the opportunity cost to society from not working on directly socially beneficial applications in fields like medicine and artificial intelligence?
My other two options are working at an ambitious new robotics startup, and a PhD in deep learning.
I have a few questions:
1) What would you say is a reasonable salary range for someone with a master's degree in computer engineering and a year of experience in back office, as well as an assortment of ML side projects? How high could you expect it to be in 2, 5, 10 years?
2) Is it very difficult to break into the industry? This opportunity just landed in my lap (recruiter), and I'd like to know how likely it is that I'll find something like it again.
3) Will a PhD in machine learning (and the resulting five year gap in the industry) make me more or less employable? How will it affect my salary/job opportunities?
4) Just how much of the job is reading and implementing machine learning papers, and how much of it is general software engineering?
5) Where can you derive meaning and satisfaction from a job in quantitative finance? How do you reconcile the opportunity cost to society from not working on directly socially beneficial applications in fields like medicine and artificial intelligence?