Amanda Casari

Amanda is endlessly fascinated (and sometimes horrified) by the difference between the systems we aim to create and the ones that emerge. She has worked in a breadth of cross-functional roles and engineering disciplines for the last 18 years, including developer relations, data science, data engineering, complexity science, and robotics. She creates projects and programs to make the data world more responsible and approachable, including co-authoring the O'Reilly book, Feature Engineering for Machine Learning Principles and Techniques for Data Scientists. She is currently leading research and data engineering to better understand risk and resilience in open source ecosystems.