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.
- 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.