Machine Learning Expert Needed for Autoencoder & PCA Analysis Improvement

I need a Machine Learning expert to refine and extend an existing dimensionality reduction analysis on a financial dataset. The current implementation includes PCA & Variational Autoencoder (VAE), but requires further modifications:

✅ Implement a third Autoencoder (e.g., Convolutional Autoencoder)
✅ Apply PCA & Autoencoders on both training and test sets and analyze generalization
✅ Compare reconstruction errors between training & test data
✅ Analyze key components/features for all four methods (PCA, VAE, Autoencoders)
✅ Fix minor visualization issues (integer axis labels, English-only text, formatting)

Requirements:
? Strong expertise in Python (TensorFlow, PyTorch, NumPy, Pandas, Scikit-learn)
? Experience with Autoencoders & Dimensionality Reduction
? Ability to deliver well-commented, clean code with clear visualizations
? Must be fluent in English