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Meet Wazir
Within my work, I love to investigate issues in a creative way. Due to my interest in quantitative data, this often involves devising a technical or practical solution to gather and/or analyse information. In doing so, the context remains of great importance.
As a researcher, I have built experience in various domains, such as telecom research for the Ministry of Economic Affairs, as well as labour market research for the Top Sectors.
In my research, I work with a wide range of data sources, including GIS data (geographical), CBS Microdata, graph data (e.g. bibliometrics), and in addition to structured data, unstructured data (text). Using tools like Python and databases (SQL), I apply various techniques to address a problem. Examples include GIS analyses, automated data collection/processing, and dashboarding.
Over time, I have also incorporated the use of AI, such as employing LLMs (large language models) for web scraping, data enrichment, and gaining insights from large amounts of textual data. This has provided me with knowledge of both the contextual content in research and 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 Eindhoven University of Technology, including a semester at the Technical University of Denmark (DTU). Following my thesis on the rollout of fibre optic connections in the Netherlands, I continued to work at Dialogic.
Outside of work, my hobbies revolve around Raspberry Pi's, (home) automation, and applications of AI models. Hence, technology and data also play a role in my leisure time.
