- Design and execute experiments to evaluate and compare the performance of different ML models using appropriate metrics.- Analyze training and test data distributions to identify potential biases, anomalies, and areas for data augmentation or preprocessing.- Thoroughly investigate ML model results, identify failure modes, and propose iterative improvements to model architecture, training, or data.