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100 Days of Machine Learning on Databricks Day 6: Key Roles in a Machine Learning Project
Machine Learning is a Team Sport
3 min read4 days ago
In 2025, enterprise Machine Learning (ML) projects are no longer side experiments. They are full-scale, cross-functional initiatives embedded in business operations.
Whether you’re predicting demand from SAP, modeling churn from Customer 360 data, or automating forecasts using Databricks — the success of your ML project depends on getting the right people in the right roles.
Today’s article breaks down the key roles in a modern ML project, with real examples from SAP + Customer 360 use cases.
Why You Need Clearly Defined Roles
Machine Learning projects involve:
- Complex data flows
- Evolving business logic
- Iterative experimentation
- Governance and compliance
Without clear responsibilities, projects fail due to poor collaboration, unclear accountability, or a broken hand-off between teams.
