During this episode, special guest, and actual data scientist, Dr. Melinda Thielbar, a Ph.D. Statistician, and I attempt to demystify data science by explaining what a data scientist does, including the requisite skills involved, bridging the communication gap between data scientists and business leaders, delivering data products business users can use on their own, and providing a straightforward explanation of key concepts such as signal-to-noise ratio, uncertainty, experimentation, and correlation.
Melinda Thielbar is the Senior Mathematician for IAVO Research and Scientific. Her work there focuses on power system optimization using real-time prediction models. She has worked as a software developer, an analytic lead for big data implementations, and a statistics and programming teacher.
Melinda Thielbar is a co-founder of Research Triangle Analysts, a professional group for analysts and data scientists located in the Research Triangle of North Carolina.
While Melinda Thielbar doesn’t specialize in a single field, she is particularly interested in power systems because, as she puts it, “A power systems optimizer has to work every time.”
Demystifying Data Science
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