A. Use Snowflake's masking policies to redact PII columns before any data is accessed for model training. Ensure role-based access control is configured so that only authorized personnel can access the unmasked data for specific purposes.

B. Create a view that selects only the non-PII columns for model training. Grant access to this view to the data science team.

C. Encrypt the entire database containing the transaction data to protect PII from unauthorized access.

D. Use Snowflake's data sharing capabilities to share the transaction data with a third-party machine learning platform for model development, without any PII masking or redaction.

E. Apply differential privacy techniques on aggregated data derived from the transaction data, before using it for model training. Combine this with Snowflake's row access policies to restrict access to sensitive transaction records based on user roles and data attributes.