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Lead the evolution of condition-based and predictive maintenance capabilities across Bombardier's global fleet
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Bombardier

Manager, Predictive Maintenance & Data Science

Dorval, QC, Canada

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: Aug 14, 2026

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

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

Reliability Engineering & Fleet Analytics

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

Data Science & Advanced Analytics

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

Team Leadership & Execution

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

Cross-functional Collaboration

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

Delivery Execution & Operational Impact

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

How to thrive in this role?

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

Assets

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

Now that you can see yourself with the Bombardier Team!

Opportunity Manager, Predictive Maintenance & Data Science

Primary Location Administrative Centre (CA)

Organization Aerospace Canada

Requisition 14646 Manager, Predictive Maintenance & Data Science

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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

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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

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