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A multinational corporation is launching a global marketing campaign and has developed a machine learning model to optimize its strategy. The campaign targets diverse demographics across multiple regions, requiring the model to handle varying data privacy laws and cultural nuances. The company aims to maximize ROI while ensuring compliance and scalability. Given these constraints, which professional is primarily responsible for ensuring the model's predictions are not only accurate but also actionable and interpretable by the marketing team across different regions? Choose the best option.
A
Marketing Analyst - Specializes in analyzing campaign performance but may lack the technical expertise to translate complex model outputs into region-specific strategies.
B
Project Manager - Ensures the project stays on schedule and within budget but may not have the technical depth to interpret model outputs for actionable insights.
C
Data Engineer - Focuses on the infrastructure and pipelines for data processing, not on deriving actionable marketing strategies from model outputs.
D
Professional Machine Learning Engineer - Works closely with the marketing team to define how model outputs should be used to address regional business challenges, ensuring predictions are actionable and compliant with local regulations.