Data Science Research Associate
Current• Leveraging multiple data sources in an inference and prediction framework. • Performing statistical validation, cross-validation, hyperparameter tuning, and model validation.• Utilizing regression approaches, including spatial autoregressive molding (SAR), random forest machine learning, and deep learning models to predict the impacts of managing sustainability/regenerative agricultural practices. • Automating complex data processes and manual input to streamline analysis and reporting by developing and using data pipelines via deep/machine learning. • Preparing and presenting findings on soil health and sustainability analysis.