Sophia Claire Zitman
About Sophia Claire Zitman
Sophia Claire Zitman is an R&D Engineer specializing in Explainable AI at Deeploy, where she conducts workshops and develops visualizations for AI projects. She holds a Master's degree in Data Science and Entrepreneurship and has experience working in various roles related to data science and economics.
Work at Deeploy
Sophia Claire Zitman serves as an R&D Engineer specializing in Explainable AI at Deeploy since 2021. In her role, she conducts hands-on workshops focused on explainable AI, enhancing understanding and application of this technology. She collaborates with her team to develop explainer visualizations for various explainable AI projects. Her work aims to improve the transparency and interpretability of AI systems, contributing to the broader goals of the organization.
Education and Expertise
Sophia holds a Master of Science in Data Science and Entrepreneurship from the Jheronimus Academy of Data Science, where she studied from 2018 to 2021. Prior to that, she earned a Bachelor of Science in Economics and Business Economics from Universiteit Maastricht, completing her studies from 2014 to 2018. Additionally, she studied at Aloysius College, achieving a Middelbare School qualification from 2008 to 2014. She also participated in an Erasmus+ program at Univerzita Karlova v Praze for one semester in 2017.
Background
Sophia has a diverse professional background that includes experience as a Data Science Intern at CZ in 2019, where she worked for one month in Tilburg, Netherlands. She also served as an Eindexamen Trainer Economie at Eindsprint in 2015 for eleven months in Eindhoven, Netherlands. Before her current role at Deeploy, she was a Graduate Intern at Enjins from 2020 to 2021, gaining valuable experience in the field of machine learning.
Current Role at Enjins
Since 2021, Sophia has been working as a Machine Learning Engineer at Enjins in Amsterdam. In this position, she focuses on projects that connect Enjins with its sister company, Deeploy, particularly in the area of explainable AI. Her role involves applying her expertise in machine learning to develop solutions that enhance the understanding and usability of AI technologies.