Lucie Woellenstein
About Lucie Woellenstein
Lucie Woellenstein serves as the Data Carpentries Course Coordinator at the Bayes Centre in Edinburgh, focusing on data carpentry and interdisciplinary research. She holds a PhD in Health in Social Science from the University of Edinburgh and has a diverse educational background in geography, geoinformation technology, and theatre studies.
Work at Bayes Centre
Lucie Woellenstein serves as the Data Carpentries Course Coordinator at the Bayes Centre in Edinburgh City, Scotland. She has held this position since 2021, focusing on the coordination of data carpentry courses. Her role involves organizing and instructing online statistics and data workshops that aim to enhance the skills of students and the Scottish workforce.
Education and Expertise
Lucie Woellenstein has a diverse educational background. She achieved her PhD in Health in Social Science from The University of Edinburgh, where she studied from 2019 to 2023. Prior to that, she earned a Master’s Degree in Geoinformation Technology & Cartography from The University of Glasgow in 2016. Additionally, she studied Theatre Studies and Geography at The University of Glasgow, obtaining her MA from 2011 to 2015. She also attended Freie Universität Berlin, focusing on Theatre Studies and Geography, and completed the International Baccalaureate at the International School of Brussels.
Background in Data Science and Geography
Lucie Woellenstein has a solid background in data science and geography. She worked as a Graduate Consultant Data Scientist at Ordnance Survey from 2017 to 2019. Prior to that, she held positions as a GIS Intern at the Adam Smith Business School and as a Data Investigator/GIS Technician at QC Data in 2016. Her experience also includes a PhD internship with the data standards team at The Scottish Government in 2021.
Research and Methodologies
Lucie Woellenstein engages in interdisciplinary research that combines social sciences with data science methodologies. She utilizes machine learning techniques in her research to address issues related to homelessness. Her work reflects a commitment to applying data-driven approaches to social science challenges.