As a Meteorological Data Scientist at Weathernet, my role revolves around harnessing the power of data to refine weather prediction models. Utilizing a robust toolkit comprising Python, Excel, and SQL, I delve into the intricacies of meteorological data, identifying biases and enhancing the accuracy of forecasts critical for weather insurance claims. This analytical venture not only supports Weathernet's operational excellence but also fuels my passion for environmental science.My academic journey as a Physics of the Environment graduate student at the University of Reading has been marked by a proactive engagement with Machine Learning and Data Science. With a focus on employing Python and Linux, I am dedicated to extending my expertise and contributing to advancements in environmental monitoring and weather prediction technologies. Our team's collaborative efforts are geared towards making significant strides in the field of meteorology in insurance.