Igor Mosyagin
After doing two PhDs, one in Theoretical Physics and one in Materials Science, I decided that maybe there was such a thing as doing too much science.
As a recovering academic, these days I work across various data roles, doing a bit of everything: engineering, modelling, machine learning, and analytics. During my time in computational research, I picked up a few practical tricks that turned out to be just as useful in industry. I enjoy sharing them because I’ve found that some of them are not as widely known in the Python and data community as I expected.
Session
Why do data engineers, analysts, managers, and ML people so often seem to talk past each other? This talk looks at the real, painful, and sometimes funny ways how misunderstanding between data roles happens and what we as data folks can do to make working together less annoying.