Podcast

PODCAST | What makes a data scientist?

Claire Schulkey
Blue monitor in front of a neon blue wall of binary numbers. By Pixabay.

"Data Scientist" is listed as the “Sexiest Job of the 21st Century” by the Harvard Business Review, but what is data science and what do data scientists do? Claire Schulkey investigated the question at International Data Week speaking with Amy Nurnberger and Sarah Callaghan, two data professionals, and she heard from the chief data scientist at the New York Times to figure out what makes a data professional, how people get into the field, and what they do all day.

PARTICIPANTS

HostClaire Schulkey, Ph.D. Computational and Systems Biology, 2015-2017 Executive Branch Fellow at the National Institutes of Health

Chris Wiggins, Ph.D., Chief Data Scientist, New York Times

Mark Parsons Research Data Alliance, Secretary General

Amy Nurnberger, Research Data Manager, Columbia University, Twitter: @DataAtCU

Sarah Callaghan, Ph.D., Senior Scientific Researcher and Project Manager, British Atmospheric Data Centre, Twitter: @sor

PRODUCER

Carlos Faraco, Ph.D. Neuroscience, 2016-17 Judicial Branch Fellow at the National Institute of Justice

Image: Pixabay

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Authors

Claire Schulkey

Schulkey, Claire: Fellowship 2016-2017 Schulkey, Claire: Fellowship 2015-2016
Claire Schulkey is a computational biologist with a background in biomedical research, specifically in the area of complex genetic disease. While completing her doctorate at Washington University in St. Louis, Claire showed the link between maternal ageing and congenital heart disease risk in offspring, and demonstrated the protective effect of maternal exercise on the developing fetus with projects involving over 18,000 mice of mixed genetic background, and computational modeling. After her PhD Claire put her computational experience to work as a post doc with Heather Lawson and developed methods to generate customized reference genomes for use in RNA-Seq and studies of parent of origin effects. In addition to next generation sequencing technologies and algorythm development, Claire is passionate about creating resources to make computational techniques accessible and understandable to wet-lab scientists. In her spare time Claire enjoys swing dance, sailing, and the culinary arts.