Developed robust prediction algorithms leveraging Python and machine learning techniques to analyze historical seed data and forecast price fluctuations, contributing to informed decision-making in agricultural markets.Designed and implemented an intuitive user interface using Streamlit, enabling stakeholders to interact with real-time prediction graphs effortlessly, thus enhancing accessibility to critical market insights.Deployed the application on GitHub, utilizing version control to ensure seamless collaboration and efficient management of project updates, facilitating continuous improvement and scalability.Collaborated closely with a professor in a research environment, demonstrating strong communication and teamwork skills while contributing to a multidisciplinary effort to understand agricultural market dynamics and drive innovation in data-driven decision-making processes.

-Big Data Analysis -Team Leadership and Modeling-Results Reporting and Recommendations -Collaboration with Development Teams