Deputy Director/Assistant Director (Data Analytics Department)

[What the role is]

This role leads the strategic direction, development, and delivery of AI solutions, aligning AI engineering initiatives with organisational goals in clean energy. This includes setting technical roadmaps, establishing governance frameworks, and driving innovation through the adoption of emerging AI technologies.

They are responsible for building and leading a high-performing AI team, fostering a culture of technical excellence, collaboration, and continuous learning across engineers, data professionals, and domain experts.

The role also oversees end-to-end AI solution delivery, ensuring robust MLOps governance, scalability, security, and reliability of AI systems in line with infrastructure and regulatory requirements.

In addition, the Branch Head manages key stakeholder relationships and strategic partnerships, effectively bridging business, technical, and regulatory needs, while ensuring strong operational oversight in budgeting, resource allocation, and successful delivery of multiple AI initiatives.

[What you will be working on]

(1)   Strategic AI Leadership and Solution Architecture: Develop and execute the AI Solutions Branch's AI engineering strategy, establishing technical roadmaps that align with EMA's clean energy vision and operational requirements. Co-lead the formulation of AI governance frameworks with CDO office. Lead formulation of solution architecture standards and risk management protocols for key energy planning applications. Drive innovation initiatives and evaluate emerging AI technologies for potential adoption across EMA's AI and GenAI portfolio.

(2)   Team Leadership and Technical Excellence: Lead, mentor, and develop a high-performing team of AI Engineers and specialists within the AI Solutions Branch. Foster a culture of innovation, continuous learning, and technical excellence whilst ensuring knowledge sharing and cross-functional collaboration with Data Scientists and Data Engineers in the department, and Subject Matter Experts in domain departments.

(3)   AI Solution Delivery and MLOps Governance: Oversee the strategic direction of AI solution development across the complete AI/ML lifecycle, ensuring production-ready solutions are delivered reliably and consistently. Establish and maintain comprehensive MLOps governance standards, including CI/CD/CT pipeline frameworks, automated retraining infrastructure, and model performance monitoring protocols. Ensure AI solutions are scalable, secure, and aligned with WOG infrastructure requirements.

Strategic Stakeholder Engagement and Partnership Management: Engage with senior leadership, internal and external stakeholders and WOG partners to communicate AI strategy, capabilities, and business outcomes. Build strategic partnerships with technology vendors, research institutions, and industry players to advance EMA's applied AI capabilities. Lead cross-functional initiatives that bridge technical solutions with business requirements and regulatory compliance. Operational Excellence and Resource Management: Oversee budget planning and resource allocation for AI engineering initiatives within the AI Solutions Branch. Ensure project delivery excellence across multiple concurrent AI/ML projects whilst managing risks, dependencies, and technical trade-offs.

[What we are looking for]

• Education in Computer Science, Mathematics, Physics, Data Science or related quantitative field. Specialised AI certifications advantageous
• Minimum 10 years of professional experience developing, deploying, and maintaining enterprise-grade AI/ML models in production environments
• Minimum 5 years of leadership experience in managing technical teams
• Proven track record of implementing enterprise-scale AI solutions in production environments
• Demonstrated ability to lead and inspire high-performing technical teams
• Strong strategic thinking and solution architecture capabilities
• Excellent stakeholder management and communication skills across all organisational levels
• Experience in budget management, resource planning, and project portfolio oversight
• Proven ability to drive technical innovation whilst maintaining operational excellence
• Deep understanding of AI/ML technologies, architectures, and implementation approaches across the full lifecycle
• Comprehensive knowledge of MLOps tools and practices at enterprise scale
• Advanced understanding of model optimisation techniques and production deployment strategies
• Strong analytical and problem-solving capabilities with focus on optimal technical trade-offs
• Ability to translate technical concepts into business value and strategic outcomes
• Experience with digital transformation initiatives and change management in technical environments