I am currently a postdoc and my PhD was in applied mathematics in the area of numerical analysis and electromagnetic/acoustic wave propagation. There was no statistical element to my PhD, it was completely deterministic. I took several probability/statistics and one machine learning module 5-6 years ago during my BSc, and a stochastic ODE module during my MSc but that's about it..its been all applied mathematics since then.
I am considering leaving academia and entering industry and it seems like there are far more jobs in the area of data science/machine learning than there are for my skillset.
- If I left academia and began 'studying up', how long do you think it could take me to gain the skills required for a data science/machine learning position in industry?
- It seems like there is a very wide variety of science/machine learning techniques and obviously there isn't time to learn all or even most of them. So what approaches are absolutely essential for data science/machine learning in industry these days and what is the most efficient route to gaining these skills?