Bernease Herman is a data scientist at WhyLabs, the AI Observability company, and a research scientist at the University of Washington eScience Institute. At WhyLabs, she is building model and data monitoring solutions using approximate statistics techniques. Earlier in her career, Bernease built ML-driven solutions for inventory planning at Amazon and conducted quantitative research at Morgan Stanley. Her academic research focuses on evaluation metrics and interpretable ML with specialty on synthetic data and societal implications. She is a PhD student at the University of Washington and holds a Bachelor’s degree in mathematics and statistics from the University of Michigan.