The Director, Data Science & AI is a senior leadership role within Air Canada’s Digital, Data, and AI organization, reporting to the Head of Data & AI. This role is accountable for leading the development, deployment, and operationalization of advanced analytics, machine learning (ML), and artificial intelligence (AI) solutions that drive measurable business value across customer experience, operations, and commercial functions.

The Director will balance visionary leadership with pragmatic execution, ensuring that all AI initiatives adhere to responsible AI principles and deliver sustained business outcomes. They will partner closely with Data Engineering, Data Product Management, and Data Platforms to ensure AI models are powered by high-quality data, deployed efficiently, and monitored for ongoing performance.

The Director will lead the following groups of employees:

Data ScientistsML EngineersAI SpecialistsMLOPs specialistsGenAI Engineers

AI Strategy & Enterprise Alignment

Lead the definition and execution of Air Canada’s enterprise AI and advanced analytics strategy, ensuring alignment with corporate objectives, regulatory requirements, and emerging technology trends.Translate high-level business priorities into a clearly sequenced portfolio of AI initiatives that deliver measurable outcomes across revenue growth, operational performance, safety, and customer satisfaction.Collaborate with the Head of Data & AI to identify areas where AI can create competitive advantage, reduce costs, or open new revenue streams.Ensure AI priorities are integrated into annual planning cycles and quarterly business reviews, with transparent value-tracking mechanisms in place.

Partner with business leaders to identify and refine high-impact AI use cases, ensuring they are grounded in clear business problems and measurable KPIs.Drive the development of AI solutions across domains such as customer personalization, dynamic pricing optimization, disruption recovery, predictive maintenance, crew planning, and fraud detection.Maintain a prioritized backlog of AI initiatives, balancing quick wins with foundational investments that enable long-term scalability.Facilitate cross-functional workshops to align on AI opportunities, feasibility, and success metrics.

Oversee the full lifecycle of AI models from problem framing and data preparation to model training, validation, deployment, and ongoing performance monitoring.Establish MLOps best practices, including automated testing, model registries, CI/CD for ML pipelines, and real-time model monitoring for drift, bias, and degradation.Ensure models are interpretable, auditable, and compliant with responsible AI principles and applicable regulations.Collaborate with Data Engineering to ensure models have access to clean, timely, and well-structured data, including real-time feeds where necessary.

Explore and operationalize generative AI (GenAI) and agentic AI capabilities, working closely with product, operations, and customer experience teams to identify breakthrough applications.Lead pilots and proofs-of-concept for emerging AI technologies, ensuring rigorous evaluation before enterprise-wide deployment.Establish guidelines for safe, secure, and ethical use of generative AI in both customer-facing and internal applications.

Partner with Data Product Management to ensure AI outputs are packaged as reusable APIs, data products, or embedded capabilities within business applications.Work with the Transformation Office to integrate AI into operational workflows, change management programs, and performance measurement frameworks.Engage with Technology, Digital, and Operations teams to ensure infrastructure, governance, and security requirements are met for all AI deployments.

Build and lead a chapter of data scientists, ML engineers, and AI specialists, creating clear role definitions, skill matrices, and career development plans.Promote a culture of continuous experimentation, measurable impact, and responsible innovation.Implement structured mentorship and training programs to accelerate team maturity and reduce dependency on external vendors.Recognize and reward contributions that directly advance Air Canada’s AI capabilities and business outcomes.

Serve as the guardian of responsible AI practices, ensuring transparency, fairness, and explainability in all deployed models.Partner with Legal, Privacy, and Risk teams to ensure compliance with evolving AI regulations and industry standards.Establish processes for regular review of AI systems to detect bias, performance drift, or unintended consequences, and implement corrective actions swiftly.

Benchspan Air Canada’s AI capabilities against industry leaders, identifying gaps and opportunities for improvement.Engage with academic institutions, AI startups, and industry consortia to stay ahead of emerging AI trends and recruit top-tier talent.Represent Air Canada at conferences, forums, and media engagements to position the organization as a leader in applied AI in aviation. 

10+ years of experience in Data & AI.A relevant University degree/technical certification, and/or relevant experience.Demonstrated ability to lead, inspire, and mentor a diverse and talented team of technology professionals.Advanced knowledge of data platforms, governance, analytics, and AI technologies.Experience with big data, machine learning, generative ai, agentic ai, and data visualization toolsExceptional leadership, stakeholder management, and communication skills, with the ability to influence at all levels, including C-level executives.Strong analytical, problem-solving, and decision-making skills, with the ability to navigate complexity and ambiguity.Experience leading operating model redesigns, cost optimization efforts, and talent strategy initiatives.Experience in leading Data and AI technologies and tools outcomes at executive levelsDemonstrate punctuality and dependability to support overall team success in a fast-paced environment.

Candidates must be eligible to work in the country of interest at the time any offer of employment is made and are responsible for obtaining any required work permits, visas, or other authorizations necessary for employment. Prior to their start date, candidates will also need to provide proof of their eligibility to work in the country of interest.

Based on equal qualifications, preference will be given to bilingual candidates.

Air Canada is strongly committed to Diversity and Inclusion and aims to create a healthy, accessible and rewarding work environment which highlights employees’ unique contributions to our company’s success.

Air Canada thanks all candidates for their interest; however only those selected to continue in the process will be contacted.