Katherine is a Data Scientist and Data Science Ambassador in the e-commerce domain, conducting both research and corporate training in AI, machine learning, Natural Language Processing (NLP) and data science. She is a speaker, writer, teacher, and passionate workaholic.
With a background in computational linguistics and (deep) machine learning, Katherine has worked in R&D for Mercedes-Benz and the Fraunhofer Institute, specialising in user interfaces and Natural Language Understanding. In her 'free' time, she is education Lead for Women in AI Upper Austria, volunteer mentor at Female Coders Linz, a trainer for Linkedin Learning, and recently co-authored the textbook, 'The Handbook of Data Science and AI'.
I should have known I was up against it when even my Kaggle solution sucked. I’d been tasked with launching our company’s research efforts into Customer Lifetime Value prediction, so naturally, I turned to that grail of tutorials and toy datasets, and started exploring. Very quickly I learned two things: the go-to CLV dataset was not worth going to, and I really needed some retail domain experts.