Elle O’Brien is a data scientist at Iterative, a startup building open source software tools for machine learning, where she works on projects including DVC and CML. Her work centers on reproducibility and engineering practices for ML, from experiment versioning to continuous integration for machine learning, a topic she has spoken about at DataTalks.Club’s conference.

Elle is also a lecturer at the University of Michigan School of Information. She completed her PhD at the University of Washington, where she conducted research on speech and hearing using mathematical models, and her route into developer relations included a viral StyleGAN project that drew her into open source community work.

Across research, industry, and teaching, Elle is broadly interested in developing methods, standards, and educational resources for anyone who works with data. She writes and speaks on reproducible machine learning, open source developer relations, and helping data science teams build tools they can trust.