Position Title

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Position Summary

• The Data Management Lead (AI/ML/API) will be responsible for managing MAG’s data platform as it lrelates to AI, ML and integration of APIs through APIs. The person will work with the Business Units and data science teams to refine and optimize data science and machine learning models, by providing the necessary foundational API, data lake and data engineering capabilities in MAG.
• This role involves managing data pipelines, ensuring data integrity and accessibility, supporting ML model deployment, and fostering collaboration across data science, engineering, and business teams. The ideal candidate will have a strong technical background in AI and ML, excellent project management skills, and experience in API development and data integration at scale.

Key Accountability

• Lead the development and execution of MAG’s data platforms for AI and machine learning initiatives.
• Oversee the end-to-end management of data pipelines, ensuring data is collected, stored, processed, and accessible for AI/ML models and other business applications.
• Ensure data quality, integrity, security, and governance across all AI, ML, and API-related projects.

• Collaborate with data scientists and machine learning engineers to manage data requirements for AI/ML model training, testing, and deployment.
• Optimize data workflows for AI/ML processes, ensuring scalability and performance in large datasets and complex environments.
• Implement and manage automated systems to monitor, evaluate, and maintain ML models in production.

• Oversee the design, development, and maintenance of APIs for data integration across platforms, systems, and applications.
• Ensure APIs are secure, reliable, and well-documented, facilitating seamless data exchange between internal and external stakeholders.
• Collaborate with engineering teams to implement best practices for API performance, versioning, and lifecycle management.

• Work closely with cross-functional teams (data science, IT, software development, data product management) to ensure data initiatives align with business goals and technical requirements.
• Provide guidance and leadership to data engineers, architects, and analysts, fostering a culture of innovation and continuous improvement.
• Act as a liaison between technical and non-technical teams to translate business requirements into technical solutions.

• Ensure compliance with relevant data privacy regulations (e.g., GDPR, PDPA, CCPA) and internal data governance policies.
• Implement robust security measures for AI/ML models, data pipelines, and APIs to protect sensitive data and intellectual property.
• Establish best practices for data management, version control, and model governance.

• Track and analyze key performance indicators (KPIs) for AI/ML models and APIs to ensure they meet organizational needs and are delivering business value.
• Provide regular reports on the status, performance, and ROI of AI, ML, and API-related projects to senior management and stakeholders.