Communicating data science: A guide to presenting your work

See the forest, see the trees. Here lies the challenge in both performing and presenting an analysis. As data scientists, analysts, and machine learning engineers faced with fulfilling business objectives, we find ourselves bridging the gap between The Two Cultures: sciences and humanities. After spending countless hours at the terminal devising a creative and elegant solution to a difficult problem, the insights and business applications are obvious in our minds. But how do you distill them into something you can communicate? Qualifications and requirements for a senior data scientist position. Presenting my work is one of the surprising challenges I faced in my recent transition from academia to life as a data analyst at a market research and strategy firm. When I was a linguistics PhD student at UCLA studying…


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