11) "Getting Smarter about Biostatistics & Data Science" (Dr. Che Smith)

Episode 11 of the Radical Math Talk podcast, hosted by Kwame Sarfo-Mensah, titled "11) "Getting Smarter about Biostatistics & Data Science" (Dr. Che Smith)" was published on May 26, 2022 and runs 61 minutes.

May 26, 2022 ·61m · Radical Math Talk

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Summary

In this week's episode, I'm thrilled to connect with my good friend Dr. Che Smith for a deep dive into personal math journey and an introduction to the world of biostatistics and data science!  To learn more about Che's work, you can connect with her on LinkedIn (https://www.linkedin.com/in/chesmith1/).   BIO: Dr. Che Smith currently serves as the Senior Analytics Engineer for Netflix.  She previously served as the visiting assistant professor of Data Science at Davidson College in North Carolina.  Che's experience spans a variety of settings, including local and federal government public health agencies, academia, consulting and entrepreneurship. As data and computation continue to be pervasive aspects of our lives, her courses introduce students to how data science and statistics are understood (or, in many cases, misunderstood) and demonstrated in our everyday lives.  Her research focuses on modeling data collected from individuals across time with attention to variable choice, bias reduction, and the use of data visualization to communicate complex and high-dimensional data.

Episode Description

In this week's episode, I'm thrilled to connect with my good friend Dr. Che Smith for a deep dive into personal math journey and an introduction to the world of biostatistics and data science! To learn more about Che's work, you can connect with her on LinkedIn (https://www.linkedin.com/in/chesmith1/).

BIO: Dr. Che Smith currently serves as the Senior Analytics Engineer for Netflix. She previously served as the visiting assistant professor of Data Science at Davidson College in North Carolina. Che's experience spans a variety of settings, including local and federal government public health agencies, academia, consulting and entrepreneurship. As data and computation continue to be pervasive aspects of our lives, her courses introduce students to how data science and statistics are understood (or, in many cases, misunderstood) and demonstrated in our everyday lives. Her research focuses on modeling data collected from individuals across time with attention to variable choice, bias reduction, and the use of data visualization to communicate complex and high-dimensional data.