Data Management

2 weeks ago

Kuala Lumpur, Kuala Lumpur, Malaysia Malaysia Airlines Full time 60,000 - 120,000 per year
Position Title

Data Manager - AI, Machine Learning, and APIs

Report To

Data Product Manager

Position Summary

The Data Management Lead (AI/ML/API) is responsible for managing MAG's data platform for AI, ML, and API integration. This role collaborates with Business Units and data science teams to refine and optimize data science and machine learning models by providing essential APIs, data lakes, and data engineering capabilities.

Key responsibilities include managing data pipelines, ensuring data integrity and accessibility, supporting ML model deployment, and fostering collaboration among 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 large-scale API development and data integration.

Key Accountability

Data Management and Strategy

  • Lead development of MAG's data platforms for AI and machine learning.
  • Oversee data pipelines to ensure effective collection, storage, processing, and accessibility for AI/ML models and other business applications.
  • Ensure data quality, integrity, security, and governance for all AI/ML projects.

AI & Machine Learning Operations

  • 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 automated systems to monitor and maintain ML models in production.

API Development and Integration

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

Collaboration and Leadership

  • Work with cross-functional teams to align data initiatives with business goals.
  • Provide guidance to data engineers and analysts, fostering innovation and improvement.
  • Serve as a liaison between technical and non-technical teams to translate requirements.

Governance, Compliance, and Security

  • Ensure compliance with data privacy regulations (e.g., GDPR, CCPA) and 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.

Performance Monitoring and Reporting

  • 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.

KPIs

  • Successful deployment and maintenance of AI/ML models in production.
  • Data accessibility and integrity across all AI and ML projects.
  • API performance and reliability metrics.
  • Compliance with data governance and security standards.
  • Business value delivered by AI/ML initiatives.

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