A developer must grant a data science team read and write access to datasets in Azure Machine Learning but must not allow them to create or delete compute clusters. Which built-in Azure RBAC role assignment is most appropriate at the Azure Machine Learning workspace level?
Select an answer to reveal the explanation.
Short Explanation
Here's the deal — you want the AzureML Data Scientist role because it lets the team read and write datasets, create and run experiments, and submit jobs without letting them create or delete compute clusters. That's the least-privilege fit for data scientists.
Full Explanation
The AzureML Data Scientist built-in role is the most appropriate because it grants permissions to perform most actions within an Azure Machine Learning workspace, including creating and running experiments, accessing datasets, and submitting jobs, while excluding management operations like creating or deleting compute infrastructure. This follows the least-privilege principle for data scientists. The Contributor role is wrong because it grants full management access, including creating and deleting compute clusters, which violates least privilege. The AzureML Compute Operator role is wrong because it is focused on starting and stopping existing compute resources, not data access. The Reader role is wrong because it is read-only and prevents writing datasets or submitting experiments.