In the new O’Reilly report Going Pro in Data Science, Jerry Overton—Distinguished Engineer and head of Advanced Analytics Research at global IT leader CSC—outlines practices for making good decisions with messy and complicated data in the real world. What he simply calls “data science that works” is a trial-and-error process of creating and testing hypotheses, gathering evidence, and drawing conclusions. These skills are far more useful for practicing data scientists than, say, mastering the details of a machine-learning algorithm.
Each chapter is ideal for current and aspiring data scientists who want to go pro, as well as IT execs and managers looking to hire in this field. The report includes:
Using scientific methods to gain competitive advantage
Why practical induction is key for thinking like a data scientist
How agile experimentation finds answers (or dead ends) much faster
Surviving (and thriving) as a data scientist in your organization