Developed an ensemble statistics submission feature for the cdcepi/FluSight-forecast-hub repository, focusing on enhancing forecasting accuracy and data submission workflows for public health planning. Leveraged Python to implement statistical modeling and data analysis techniques, ensuring that forecast submissions are both traceable and ready for future ensemble expansions. The work improved situational awareness by enabling more robust and transparent forecasting processes, supporting decision-making in epidemiological contexts. Throughout the month, the developer concentrated on building out this core functionality without addressing bug fixes, demonstrating depth in forecasting and statistical modeling while laying a solid foundation for subsequent feature development in the application.