Head, AI Semantic Modeling

 

 

 

Requisition ID: 255624

 Salary Range:  -  

Please note that the Salary Range shown is a guideline only. Salary offered may vary based on factors, including, but not limited to, the successful candidate’s relevant knowledge, skills, and experience.

 

Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

 

 

Purpose

 

 

Scotiabank is seeking a visionary leader to serve as the Head of AI Semantic Modeling, guiding the development and implementation of semantic capabilities that will drive transformative AI adoption across our organization. This role is pivotal in aligning our data strategies with cutting-edge AI technologies, ensuring our data assets are leveraged for innovation and strategic advantage. A core mandate of this role will lead Scotiabank's efforts to design, deploy, and manage the semantic layer that underpins AI capabilities. This role ensures our data is not only trusted but also semantically rich, enabling machines and humans to interpret data effectively for decision-making across diverse business areas.

 

What You'll Do

 

 

• Collaborate with cross-functional teams to define and implement the enterprise-wide semantic layer, aligning it with AI capabilities.
• Ensure semantic assets are machine-consumable and policy-aware, supporting AI use cases such as RAG (Retrieval-Augmented Generation) and decision-making workflows.
• Influence senior management on integrating semantic strategies into AI roadmaps, driving innovation in data-driven AI solutions.
• Lead the development of platforms that support semantic data modeling, metadata management, and lineage tracking for scalable AI applications.
• Oversee modernization efforts to replace outdated systems with robust semantic platforms.
• Foster a culture of excellence in engineering across global teams, ensuring consistent application of semantic principles.
• Ensure compliance with enterprise standards and frameworks governing AI use cases, including explainability and audit trails for regulatory reporting.
• Implement governance strategies that align semantic capabilities with risk management practices to support compliant AI deployment.
• Build a high-performing engineering organization focused on semantic data solutions, attracting and retaining top talent with innovative opportunities.
• Shape enterprise architecture and strategy in alignment with the bank's AI vision, ensuring seamless integration of semantic capabilities.
• Act as a trusted partner to senior leaders across Data, AI, and Technology, influencing strategic decisions through data-centric insights.
• Represent our engineering efforts in regulatory and organizational forums, contributing to global best practices in semantic layer development.

 

 

What You'll Bring

 

 

• Experience in data modeling or semantic layer design, with a focus on large regulated organizations.
• Proficiency in AI/ML, cloud platforms (Azure/AWS), DevOps, metadata management, and governance frameworks.
• Experience designing scalable solutions for AI semantics, including feature and metric definitions.
• Strong understanding in conceptual, logical, physical, and semantic data modeling.
• Advanced SQL and strong command of analytics and AI data consumption patterns, including LLM and ML workloads.
• Experience with modern cloud data platforms (Azure or AWS) and lakehouse architecture.
• Experience building batch and streaming data pipelines and AI-ready data products.
• Strong understanding of metadata, lineage, access control models, and AI governance.
• Familiarity with DevOps, CI/CD, and Agile delivery practices.
• Bachelor’s degree in computer science / engineering, data science, or mathematics / statistics
• Master’s degree in, machine learning, artificial intelligence, data science or related technical field is preferred.

 

 

 

Interested?

 

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