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Business translator

As explained in Delivering Machine Learning Projects: From design to deployment

A business translator is a project role that bridges domain stakeholders and machine-learning specialists by interpreting business needs and technical implications.

A business translator bridges domain stakeholders and machine-learning specialists. The role often draws on business analysis or software engineering experience combined with an understanding of ML systems. Its practical value is gathering user and stakeholder insights, developing them for the team leader, and keeping technical work connected to business needs. section 3.2.2

Staffing decision

A client acting as product owner may handle this work. If the product owner cannot devote time to detailed business investigations, assign a specialist. Define the tasks and time required rather than assuming the role needs a separate hire: its contribution can overlap with that of ML engineers and data scientists. section 3.2.2

How Delivering Machine Learning Projects: From design to deployment covers it

How deep it goes
Defines the role and gives a staffing decision, but leaves its distinct contribution to ML projects unresolved.
Examples
Contrasts a client product owner handling investigations with hiring a specialist when the owner lacks time.
What you can do after
Evaluate staffing needs by identifying stakeholder-investigation tasks, available product-owner time, and overlap with ML specialists.
How it connects
Connects business analysis, software engineering, product ownership, data science, and ML engineering.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Delivering Machine Learning Projects: From design to deployment. The section links point to the parts of the book it draws on.