Title: Hi HN, long time lurker with a throwaway here:<p>I recently quit academia (social sciences) and I plan to transition into a data science career within the next year or so. This is the part I liked about my academic job and the stuff I am good at (statistics, analytical problem solver, data wrangling&#x2F;modeling).<p>Reading through job ads the technical skill palette for DS seems overwhelming: python (+pandas, scikit, ...), R, docker, k8s, PowerBI, Tableau, PostgreSQL, DevOps&#x2F;pipelines, different cloud providers, maybe add some javascript, various ML toolkits (Tensorflow, etc.).<p>I have 15 years of experience as a statistician (R&#x2F;STATA&#x2F;Linux&#x2F;SQL) and a sabbatical year in front of me, which new skill(s) should I learn&#x2F;prioritize?<p>Edit: I have a PhD.<p>Thanks!
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