For Danielle Dean, data science started with psychology. “I pursued a Ph.D. in Quantitative Psychology because I was intrigued by how mathematics and statistics can be used to study individual behavior on a large scale.”
That sounds a lot like what we now call data science. “I learned how to think about data measurement, analysis and visualization and use the technologies — programming languages and tools — that enable it,” she says. It was a good fit for her work in the Artificial Intelligence and Research group at Microsoft where she leads a cross-disciplinary team — there are representatives from physics, oceanography, computer science, statistics and neuroscience — of data scientists and engineers in building predictive analytics and machine learning solutions.
Author: Christina Tynan-Wood