Worked on the XENONnT/fuse repository to deliver a Waveform Noise Sampling Improvement, focusing on enhancing the accuracy of waveform generation for scientific data analysis. Introduced a noise offset mechanism in the waveform generation process using Python, which addressed systematic bias in noise sampling and improved the reliability of downstream analyses and calibrations. The approach centered on scientific computing techniques to ensure higher data quality for physics research. Efforts during this period were dedicated to feature development and code quality, with no major bug fixes, demonstrating a methodical and targeted engineering process that strengthened the foundation for future analytical work.