In my work, I like to investigate issues in a creative way. Due to my interest in quantitative data, this often involves devising a technical or practical solution to collect and/or analyze information. However, the context remains crucial. As a researcher, I have accumulated experience in various domains, such as telecom research for the Ministry of Economic Affairs, as well as labor market research for the Topsectors. In my research, I work with a wide range of data sources, including GIS data (geographic), CBS Microdata, graph data (including bibliometrics), and both structured and unstructured data (text). Using tools like Python and databases (SQL), I apply various techniques such as GIS analyses, automated data collection/processing, and dashboarding to address research questions. Over time, I have also started utilizing AI techniques, such as employing large language models (LLMs) for web scraping, data enrichment, and gaining insights from large amounts of textual data. This has allowed me to develop expertise in understanding the contextual content in research as well as the application and possibilities of data (analyses) within it. I have completed a Bachelor's degree in Sustainable Innovation and a Master's degree in Innovation Sciences at the Technical University Eindhoven, with a semester at the Technical University of Denmark (DTU). After writing my thesis on the rollout of fiber optic connections in the Netherlands, I joined Dialogic. Outside of work, I enjoy tinkering with Raspberry Pi's, (home) automation, and AI model applications as hobbies. Technology and data also play a role in my free time.