Manager, Predictive Maintenance & Data Science

Bombardier Manager, Predictive Maintenance & Data Science

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

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

See also