Juliet Hougland is a data scientist at Cloudera, and contributor/committer/maintainer for the Sparkling Pandas project. Her commercial applications of data science include developing predictive maintenance models for oil and gas pipelines at Deep Signal, and designing/building a platform for real-time model application, data storage, and model building at WibiData. Juliet was the technical editor for Learning Spark by Karau et al. and Advanced Analytics with Spark by Ryza et al. She holds an M.S. in applied mathematics from the University of Colorado, Boulder and graduated Phi Beta Kappa from Reed College with a BA in math-physics.