Manager, Predictive Maintenance & Data Science
- Dorval, QC, Canada
Full-time
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Job details
- Job type
- Full-time
- Posting language
- English
- Posted
Original job description
Why join us?
At Bombardier, we design, build and maintain the world’s peak-performing aircraft for the world’s most discerning people and businesses, governments and militaries. We have been successful in setting the highest standards by putting our people at the heart of it all, and defining excellence, together.
Providing services to Bombardier means operating at the highest level. Every day, you are part of a team that delivers superior experiences and products, pushing the boundaries of what's possible in our industry and beyond. By prioritizing continuous growth and development, we empower everyone to reach their full potential on their own terms, because the greatest results happens when you are free to be yourself and share your unique expertise.
What are your contributions to the team?
Predictive Maintenance Strategy & Innovation
As our ideal candidate, you have:
Opportunity Manager, Predictive Maintenance & Data Science
Primary Location Administrative Centre (CA)
Organization Aerospace Canada
Requisition 14646 Manager, Predictive Maintenance & Data Science
At Bombardier, we design, build and maintain the world’s peak-performing aircraft for the world’s most discerning people and businesses, governments and militaries. We have been successful in setting the highest standards by putting our people at the heart of it all, and defining excellence, together.
Providing services to Bombardier means operating at the highest level. Every day, you are part of a team that delivers superior experiences and products, pushing the boundaries of what's possible in our industry and beyond. By prioritizing continuous growth and development, we empower everyone to reach their full potential on their own terms, because the greatest results happens when you are free to be yourself and share your unique expertise.
What are your contributions to the team?
Predictive Maintenance Strategy & Innovation
- Define and execute the Connected Aircraft predictive maintenance strategy and capability roadmap aligned with business objectives and customer needs
- Lead the evolution of condition-based and predictive maintenance capabilities across Bombardier's global fleet
- Identify opportunities to leverage aircraft operational, maintenance, and health monitoring data to improve fleet performance and maintenance outcomes
- Promote innovation through advanced analytics, artificial intelligence, and emerging technologies in support of Connected Aircraft solutions
- Lead initiatives aimed at improving aircraft reliability, dispatch availability, and maintenance effectiveness
- Oversee fleet health monitoring activities and identify emerging trends, degradation patterns, and operational risks
- Guide reliability investigations and root cause analyses to support corrective actions and product improvements
- Ensure development and continuous improvement of Condition Monitoring Events (CMEs), reliability indicators, and predictive maintenance methodologies
- Lead teams responsible for data science, machine learning, engineering analytics, and predictive maintenance solutions
- Promote the development and deployment of analytical models that generate actionable and operationally relevant insights
- Ensure predictive models and analytics solutions are technically sound, explainable, scalable, and aligned with customer and business objectives
- Collaborate with Data Platform and Software Development teams to industrialize and operationalize advanced analytics capabilities
- Lead and develop a multidisciplinary team including Data Scientists, Machine Learning Engineers, Data Engineers, Aircraft Reliability Specialists, and external partners
- Define team objectives, monitor performance, and support employee development, engagement, and career growth
- Recruit and develop capabilities aligned with long-term business and technology strategies
- Foster a culture of innovation, collaboration, technical excellence, and continuous learning
- Collaborate closely with Product Managers and Software Development teams to transform predictive maintenance concepts into customer-facing digital capabilities
- Partner with AHMS Engineering, Technical Services, Customer Response Center (CRC), Field Service Representatives (FSRs), and aircraft systems specialists to ensure operational needs are reflected in analytics solutions
- Work with suppliers, engineering teams, and external research partners to advance predictive maintenance and reliability initiatives
- Support customer engagement activities related to predictive maintenance solutions and fleet health management
- Ensure analytics initiatives and predictive maintenance capabilities are delivered on schedule and aligned with business priorities
- Define and track key performance indicators related to fleet reliability, maintenance effectiveness, customer adoption, and business value
- Monitor solution performance and continuously improve predictive maintenance capabilities based on operational feedback and measured outcomes
- Manage team budget, resource allocation, external partnerships, and vendor relationships
As our ideal candidate, you have:
- University degree in Aerospace Engineering, Mechanical Engineering, Systems Engineering, Reliability Engineering, Computer Science, Data Science, or a related field
- Minimum of 10 years of experience in aerospace engineering, reliability engineering, predictive maintenance, data science, or related domains
- Minimum of 5 years of experience leading technical or multidisciplinary teams
- Experience working with aircraft systems, maintenance operations, reliability programs, fleet performance, or aircraft health monitoring solutions
- Strong business and strategic mindset with the ability to translate technical capabilities into customer and business value
- Strong communication and stakeholder management skills, with the ability to engage both technical and business audiences
- Experience with Aircraft Health Monitoring Systems (AHMS) and Connected Aircraft technologies
- Experience with machine learning, artificial intelligence, and advanced analytics solutions
- Experience with condition-based maintenance, predictive maintenance, reliability analysis, or MSG-3 methodologies
- Familiarity with cloud analytics platforms, Python, SQL, and modern data environments
- Experience collaborating with research institutions, industry working groups, or innovation programs
Opportunity Manager, Predictive Maintenance & Data Science
Primary Location Administrative Centre (CA)
Organization Aerospace Canada
Requisition 14646 Manager, Predictive Maintenance & Data Science
More about this job
Responsibilities
Lead the strategy and execution of connected aircraft predictive maintenance and fleet health monitoring to improve aircraft reliability. Manage a multidisciplinary team of data scientists and engineers to develop scalable analytical models and digital capabilities.
Requirements
Requires a university degree in engineering or data science with at least 10 years of experience in aerospace reliability or predictive maintenance. Must have at least 5 years of experience leading technical teams and a strong background in aircraft systems.
Skills
- Predictive Maintenance
- Data Science
- Machine Learning
- Reliability Engineering
- Fleet Analytics
- Condition-Based Maintenance
- Stakeholder Management
- Team Leadership
- Aircraft Health Monitoring
- Root Cause Analysis
- Strategic Planning
- Python
- SQL
- Cloud Analytics
- Aerospace Engineering
- MSG-3 Methodologies
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Engineering
- Management & Leadership
- Transportation
- Manufacturing
Keywords
- Predictive Maintenance
- Data Science
- Machine Learning
- Reliability Engineering
- Fleet Health Monitoring
- Condition Monitoring Events
- AHMS
- Connected Aircraft
- Python
- SQL
- Cloud Analytics
- MSG-3
- Aerospace Engineering
- Root Cause Analysis
- Artificial Intelligence
- Advanced Analytics
- Aviation
- Fleet Performance
- Digital Capabilities
- Engineering Analytics