Product Manager, Artificial Intelligence, Air Canada

Air Canada is seeking a talented individual to join one of their dynamic AI project teams! As part of this team, you’ll be on the leading edge of innovation, collaborating with a diverse group of specialists – data scientists, data developers, operations research experts, machine learning engineers, and delivery leads. Your mission: to leverage machine learning (ML) and optimization techniques to create cutting-edge solutions for internal units across Commercial, Operations, or Corporate sectors.

This is your chance to make a real difference at Air Canada. Your work will have a tangible impact on their operations, and you’ll gain invaluable experience alongside a talented team at the forefront of AI. If you’re an ML or optimization whiz who thrives in collaboration, then Air Canada wants to hear from you.

Responsibilities

• Articulate the technical requirements of the project and communicate them clearly to stakeholders.
• Define key features that can be delivered to achieve the business objectives envisioned by the business product owner.
• Partner with business teams to understand and document their business processes, then translate that into business requirements, features, enhancements, etc.
• Maintain the product backlog using functional decomposition to create a well-organized, value-driven framework.
• Partner with the business product owner to identify priorities, and use that to organize user stories, plan deliverables, milestones, and releases.
• Become the liaison between the development team and the business users and stakeholders, supporting development activities.
• Translate business requirements into technical user stories that the development team can implement, translate the questions of development team into business questions that the business can address, and integrate clarification and feedback from the business to enrich the business requirements and user stories.
• Define the requirements for wireframes and personas and user experience for application side.
• Define non-functional requirements, i.e., accessibility, adaptability availability, compliance tolerance, etc.
• Act as communication broker within the business community and therefore help the development teams find the right people to work with.
• Produce data visualizations and dashboards to communicate insights on the results from the AI models to business stakeholders.
• Capture and document business questions on the explainability of AI models, analyze data in detail, and prepare documentation to respond to these investigations in a clear format.
• Partner with the business product owner to identify acceptance criteria and acceptance tests.
• Partner with the business stakeholders to validate requirements, document acceptance criteria, and connect with testing groups during UAT to review and validate the setup of the testing strategy.
• Provide feedback on the incremental results generated by the development team every sprint.

Qualifications

• Master’s degree, preferably in Engineering, Computer Science, Business Analytics, Statistic or Mathematics, or bachelor’s degree with relevant experience commensurate to the role.
• 5+ years experience in a product role or a technical role that assumed high interface with business stakeholders.
• Certifications in business analytics, such as CBAP (Certified Business Analysis Professional), data science, or artificial intelligence would be a plus.
• Proficient in hands-on data manipulation, querying, deep dive analysis, working with data from multiple sources to gain and deliver insights.
• Experience with data visualization tools such as Tableau or PowerBI, Plotly, etc.
• Proficiency in using query languages such as SQL, Python, etc.
• Knowledge of cloud computing platforms (Microsoft Azure, AWS, Google Cloud).
• Experience working in an Agile team environment.
• Ability to foster teamwork, and to effectively drive cross-team solutions that have complex dependencies and requirements.
• Experience leading and facilitating workshops with business stakeholders.
• Strong presentation skills, with the ability to explain complex analytical concepts to a non-technical audience.
• Ability to proactively identify risks and recommend potential mitigations or contingencies.
• Flexibility and resilience to work under tight deadlines and adjust to rapidly changing conditions.
• Ability to notice, interpret, and anticipate others’ concerns or reactions and communicate with them empathetically.
• Bias to action in search of business objectives with focus on meeting customer expectations.