[rbartelme]

I recently made the transition from academia to industry (also a PhD holder). I would echo a lot of what other commenters said about learning python and the associated data science tooling. Coming from an R heavy scientific discipline (quantitative ecology), I found python to be quite a bit better at things that base R struggled with, particularly string manipulations.

Aside from programmatic and cloud tools as identified in your post, one of the biggest hurdles is whittling down your academic CV into a resume. Spending time re-framing your academic accomplishments in the short form will be the best time investment for getting in for interviews. I ended up following the google XYZ resume formula: https://www.inc.com/bill-murphy-jr/google-recruiters-say-the... It kind of hurts to distill your academic achievements into "Published [X] peer reviewed papers [Y] by driving the analysis [Z]", but I think it really helped me start getting calls vs. desk rejects. Relatedly, only include publications that either highlight your expertise for a specific job posting or if they further highlight your expertise in statistics in a way that could set you apart from other candidates.