Data-Driven Video Content

Be yourself” was just one of the many career tips Caitlin Smallwood shared during a conversation with Stanford professor and Women in Data Science podcast host, Margot Gerritsen. Smallwood urges up-and-coming data scientists to explore “the avenues and nooks and crannies” of the discipline and avoid limiting themselves to the most obvious paths.

Smallwood is passionate about data-driven content and predicts that deep learning will continue to propel advances in applied data science in the future, specifically in the area of machine translation. It will take some time, she says, but machine translation would allow users to watch a movie or video and understand the subtleties of language and culture at a deeper level through nuances in inflection appropriate for different languages.

Smallwood is interested in the ways that data science guides content and helps people “understand regions and cultures around the world through storytelling.” She enjoys the fact that her job allows her to engage and learn as well.“I, myself, have learned so many things from watching different pieces of content. You learn something that’s much more subliminal or that can really impact your empathy when you relate to a character and see the details of how they live their lives in an entirely different culture. And that’s different than reading a news article about a culture,” she says.