Hilary Parker is a Data Scientist on the styling recommendations team at Stitch Fix, a personal styling service that uses a combinations of human stylists and algorithmic recommendations to help people find what they love. At Stitch Fix, she focuses on what sorts of data to collect from clients in order to optimize clothing recommendations, as well as building out prototypes of algorithms or entirely new products based on new data sources. She is also a co-founder of the Not So Standard Deviations podcast, a bi-weekly data science podcast with Roger Peng that has over half a million downloads. Their topics of discussion include the R ecosystem, recent developments in the data science and statistics field, reproducibility and the "how" of how data scientists and statisticians work. Hilary recently authored the paper Opinionated Analysis Development based on discussions from the podcast. Prior to her career in the tech field, Hilary received her PhD in Biostatistics from Johns Hopkins School of Public Health. She lives at the San Francisco Zen Center with her partner, a Soto Zen Priest. In her free time, she enjoys exploring her home of 2 years, San Francisco.
Using Data Effectively: Beyond Art and Science
Data is the lifeblood of every organization. Whatever our job title, each of us uses data to get our job done -- from observing a running system to improving performance to building a machine-learned model. This talk is about approaches and techniques to collect the most useful data we can, analyze it in a scientific way, and use it most effectively to drive actions and decisions. Is using data effectively an art or a science? It is both. The “art” helps us decide the “right” way to approach an analysis or an algorithm. The “science” applies statistical rigor to our inferences. But with only the art and the science, we miss something critically important. In this talk, I suggest that, beyond both art and science, the fundamental questions we need to ask of our data should be informed by the field of design and design thinking. Every designer needs to understand their intended user, whether they are designing a physical object, experimenting on a recommendation system, or making a launch decision about a product. That focus on the why -- instead of just the how and the what -- takes us to the next level. This talk with leave you with actionable insights about how to apply the lens of design thinking to help you use data more effectively in your everyday job.