Predictive Maintenance & Analytics Transformation Specialist
Airbus
Predictive Maintenance & Analytics Transformation Specialist
Job Description
Job Description:
We are seeking a highly skilled Predictive Maintenance Specialist with strong expertise in Aircraft Systems, Data Analytics, and Artificial Intelligence (AI). The ideal candidate will drive the development and implementation of predictive maintenance models and data-driven solutions to enhance aircraft reliability, reduce unscheduled downtime, and optimize maintenance operations.
The candidate will join Health Management and Predictive Analytic team.
The analytics approach can have several applications, such as the anticipation of the failure of an aircraft component, the diagnosis of a failure that has already occurred, what is the triggering process, detect an anomaly in the system, predict the life time of a component, find the root cause of a failure, optimize troubleshooting tasks, etc.
Main responsabilities
- Drive the design, develop and deploy predictive maintenance models to anticipate aircraft component failures and optimize maintenance schedules.
- Establish and maintain data integrity requirements to ensure the data set needed to feed the predictive maintenance models.
- Participate in defining the certification basis for CBM applications ensuring compliance with aviation authorities and alignment with safety and reliability objectives
- Integrate and analyze flight data, health monitoring system (HMS) outputs, sensor data, and maintenance logs.
- Collaborate with avionics, propulsion, and airframe engineering teams to interpret system behaviors and identify degradation patterns.
- Develop dashboards, KPIs, and data pipelines for real-time maintenance insights.
- Implement data preprocessing, feature engineering, and anomaly detection methods.
- Lead the validation and continuous improvement of predictive algorithms in operational environments.
- Support digital twin and reliability-centered maintenance (RCM) initiatives.
- Ensure compliance with aviation standards in predictive maintenance applications.
- Communicate technical findings to non-technical stakeholders through clear visualizations and reports.
- Analysis of the aircraft problems also from a Systems Engineering point of view: it is important to understand the operation of the system and the possible contributions to system failures.
- Documentation, preparation and exposition of presentations to show and communicate the model development process and the results obtained graphically and visually.
- Master’s degree in Engineering, Data Science, Artificial Intelligence, or a related field.
- 5+ years of experience in predictive maintenance, reliability engineering, or data analytics within the aviation sector.
- Deep understanding of aircraft systems (avionics, engines, hydraulics, pneumatics, environmental control, etc.).especially valuable mainly A400M, MRTT , M&L and new developments.
- Proficiency with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and data analytics tools (Python, SQL, MATLAB).
- Experience with big data architectures (e.g., Spark, Hadoop, or cloud-based analytics environments such as AWS, Azure, or GCP).
- Strong background in signal processing, time-series analysis, and fault detection.
- Good communication skills, assertiveness and willingness to travel
- Commitment, proactiveness and Team spirit is a must.
Preferred Qualifications:
- Experience with digital twin technology or fleet-level predictive maintenance programs.
- Knowledge of aircraft health monitoring systems (AHMS) and prognostics & health management frameworks.
- Knowledge in CBM (Condition-Based Maintenance)
- Familiarity with ARINC, AFDX and ATA standards for aircraft data exchange.
- Experience integrating AI models with maintenance information systems (MIS) or enterprise asset management (EAM) platforms.
- Data analytics: data cleaning, manipulation and processing. Descriptive, diagnostic, predictive and prescriptive analytics focused on aircraft systems, using techniques for pattern recognition, data mining, design of experiments, etc.
- Knowledge of AI techniques or development of complex algorithms focused on time series, NLP and image processing.
- Programming knowledge: advanced level of Python and its main libraries dedicated to analytics and data science such as Pandas, Numpy, Matplotlib, Seaborn, Bokeh, Scipy, Scikit-learn, Tensorflow, Keras, NLTK, SQLAlchemy.
- Knowledge in handling tools dedicated to data visualization such as Spotfire, Tableau, PowerBI…
- Knowledge in the development of queries for the extraction and manipulation of data: SQL.
- Basic knowledge of relational and non-relational databases.
- Knowledge of GIT, version control and collaborative development.
- General knowledge of the complete V&V development cycle.
This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.
Company:
Airbus Defence and Space SAUEmployment Type:
Permanent-------
Experience Level:
ProfessionalJob Family:
Computing&Comm and Info& Data Processing <JF-EN-EB>By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.
Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.
Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to emsom@airbus.com.
At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.
Locations
- Getafe Area,
Salary
55,000 - 85,000 EUR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Proficiency with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and data analytics tools (Python, SQL, MATLAB)intermediate
- Experience with big data architectures (e.g., Spark, Hadoop, or cloud-based analytics environments such as AWS, Azure, or GCP)intermediate
- Strong background in signal processing, time-series analysis, and fault detectionintermediate
- Good communication skillsintermediate
- Assertivenessintermediate
- Willingness to travelintermediate
- Commitmentintermediate
- Proactivenessintermediate
- Team spiritintermediate
Required Qualifications
- Master’s degree in Engineering, Data Science, Artificial Intelligence, or a related field (experience)
- 5+ years of experience in predictive maintenance, reliability engineering, or data analytics within the aviation sector (experience)
- Deep understanding of aircraft systems (avionics, engines, hydraulics, pneumatics, environmental control, etc.), especially valuable mainly A400M, MRTT, M&L and new developments (experience)
Preferred Qualifications
- Experience with digital twin technology or fleet-level predictive maintenance programs (experience)
- Knowledge of aircraft health monitoring systems (AHMS) and prognostics & health management frameworks (experience)
- Knowledge in CBM (Condition-Based Maintenance) (experience)
- Familiarity with ARINC, AFDX and ATA standards for aircraft data exchange (experience)
- Experience integrating AI models with maintenance information systems (MIS) or enterprise asset management (EAM) platforms (experience)
- Data analytics: data cleaning, manipulation and processing. Descriptive, diagnostic, predictive and prescriptive analytics focused on aircraft systems, using techniques for pattern recognition, data mining, design of experiments, etc. (experience)
- Knowledge of AI techniques or development of complex algorithms focused on time series, NLP and image processing (experience)
- Programming knowledge: advanced level of Python and its main libraries dedicated to analytics and data science such as Pandas, Numpy, Matplotlib, Seaborn, Bokeh, Scipy, Scikit-learn, Tensorflow, Keras, NLTK, SQLAlchemy (experience)
- Knowledge in handling tools dedicated to data visualization such as Spotfire, Tableau, PowerBI (experience)
- Knowledge in the development of queries for the extraction and manipulation of data: SQL (experience)
- Basic knowledge of relational and non-relational databases (experience)
- Knowledge of GIT, version control and collaborative development (experience)
- General knowledge of the complete V&V development cycle (experience)
Responsibilities
- Drive the design, develop and deploy predictive maintenance models to anticipate aircraft component failures and optimize maintenance schedules
- Establish and maintain data integrity requirements to ensure the data set needed to feed the predictive maintenance models
- Participate in defining the certification basis for CBM applications ensuring compliance with aviation authorities and alignment with safety and reliability objectives
- Integrate and analyze flight data, health monitoring system (HMS) outputs, sensor data, and maintenance logs
- Collaborate with avionics, propulsion, and airframe engineering teams to interpret system behaviors and identify degradation patterns
- Develop dashboards, KPIs, and data pipelines for real-time maintenance insights
- Implement data preprocessing, feature engineering, and anomaly detection methods
- Lead the validation and continuous improvement of predictive algorithms in operational environments
- Support digital twin and reliability-centered maintenance (RCM) initiatives
- Ensure compliance with aviation standards in predictive maintenance applications
- Communicate technical findings to non-technical stakeholders through clear visualizations and reports
- Analysis of the aircraft problems also from a Systems Engineering point of view: it is important to understand the operation of the system and the possible contributions to system failures
- Documentation, preparation and exposition of presentations to show and communicate the model development process and the results obtained graphically and visually
Benefits
- general: Flexible working arrangements to stimulate innovative thinking
- general: Commitment to workforce diversity and inclusive working environment
- general: Equal opportunities for all
Tags & Categories
Answer 10 quick questions to check your fit for Predictive Maintenance & Analytics Transformation Specialist @ Airbus.
Related Books and Jobs
Predictive Maintenance & Analytics Transformation Specialist
Airbus
Predictive Maintenance & Analytics Transformation Specialist
Job Description
Job Description:
We are seeking a highly skilled Predictive Maintenance Specialist with strong expertise in Aircraft Systems, Data Analytics, and Artificial Intelligence (AI). The ideal candidate will drive the development and implementation of predictive maintenance models and data-driven solutions to enhance aircraft reliability, reduce unscheduled downtime, and optimize maintenance operations.
The candidate will join Health Management and Predictive Analytic team.
The analytics approach can have several applications, such as the anticipation of the failure of an aircraft component, the diagnosis of a failure that has already occurred, what is the triggering process, detect an anomaly in the system, predict the life time of a component, find the root cause of a failure, optimize troubleshooting tasks, etc.
Main responsabilities
- Drive the design, develop and deploy predictive maintenance models to anticipate aircraft component failures and optimize maintenance schedules.
- Establish and maintain data integrity requirements to ensure the data set needed to feed the predictive maintenance models.
- Participate in defining the certification basis for CBM applications ensuring compliance with aviation authorities and alignment with safety and reliability objectives
- Integrate and analyze flight data, health monitoring system (HMS) outputs, sensor data, and maintenance logs.
- Collaborate with avionics, propulsion, and airframe engineering teams to interpret system behaviors and identify degradation patterns.
- Develop dashboards, KPIs, and data pipelines for real-time maintenance insights.
- Implement data preprocessing, feature engineering, and anomaly detection methods.
- Lead the validation and continuous improvement of predictive algorithms in operational environments.
- Support digital twin and reliability-centered maintenance (RCM) initiatives.
- Ensure compliance with aviation standards in predictive maintenance applications.
- Communicate technical findings to non-technical stakeholders through clear visualizations and reports.
- Analysis of the aircraft problems also from a Systems Engineering point of view: it is important to understand the operation of the system and the possible contributions to system failures.
- Documentation, preparation and exposition of presentations to show and communicate the model development process and the results obtained graphically and visually.
- Master’s degree in Engineering, Data Science, Artificial Intelligence, or a related field.
- 5+ years of experience in predictive maintenance, reliability engineering, or data analytics within the aviation sector.
- Deep understanding of aircraft systems (avionics, engines, hydraulics, pneumatics, environmental control, etc.).especially valuable mainly A400M, MRTT , M&L and new developments.
- Proficiency with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and data analytics tools (Python, SQL, MATLAB).
- Experience with big data architectures (e.g., Spark, Hadoop, or cloud-based analytics environments such as AWS, Azure, or GCP).
- Strong background in signal processing, time-series analysis, and fault detection.
- Good communication skills, assertiveness and willingness to travel
- Commitment, proactiveness and Team spirit is a must.
Preferred Qualifications:
- Experience with digital twin technology or fleet-level predictive maintenance programs.
- Knowledge of aircraft health monitoring systems (AHMS) and prognostics & health management frameworks.
- Knowledge in CBM (Condition-Based Maintenance)
- Familiarity with ARINC, AFDX and ATA standards for aircraft data exchange.
- Experience integrating AI models with maintenance information systems (MIS) or enterprise asset management (EAM) platforms.
- Data analytics: data cleaning, manipulation and processing. Descriptive, diagnostic, predictive and prescriptive analytics focused on aircraft systems, using techniques for pattern recognition, data mining, design of experiments, etc.
- Knowledge of AI techniques or development of complex algorithms focused on time series, NLP and image processing.
- Programming knowledge: advanced level of Python and its main libraries dedicated to analytics and data science such as Pandas, Numpy, Matplotlib, Seaborn, Bokeh, Scipy, Scikit-learn, Tensorflow, Keras, NLTK, SQLAlchemy.
- Knowledge in handling tools dedicated to data visualization such as Spotfire, Tableau, PowerBI…
- Knowledge in the development of queries for the extraction and manipulation of data: SQL.
- Basic knowledge of relational and non-relational databases.
- Knowledge of GIT, version control and collaborative development.
- General knowledge of the complete V&V development cycle.
This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.
Company:
Airbus Defence and Space SAUEmployment Type:
Permanent-------
Experience Level:
ProfessionalJob Family:
Computing&Comm and Info& Data Processing <JF-EN-EB>By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.
Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.
Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to emsom@airbus.com.
At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.
Locations
- Getafe Area,
Salary
55,000 - 85,000 EUR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Proficiency with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and data analytics tools (Python, SQL, MATLAB)intermediate
- Experience with big data architectures (e.g., Spark, Hadoop, or cloud-based analytics environments such as AWS, Azure, or GCP)intermediate
- Strong background in signal processing, time-series analysis, and fault detectionintermediate
- Good communication skillsintermediate
- Assertivenessintermediate
- Willingness to travelintermediate
- Commitmentintermediate
- Proactivenessintermediate
- Team spiritintermediate
Required Qualifications
- Master’s degree in Engineering, Data Science, Artificial Intelligence, or a related field (experience)
- 5+ years of experience in predictive maintenance, reliability engineering, or data analytics within the aviation sector (experience)
- Deep understanding of aircraft systems (avionics, engines, hydraulics, pneumatics, environmental control, etc.), especially valuable mainly A400M, MRTT, M&L and new developments (experience)
Preferred Qualifications
- Experience with digital twin technology or fleet-level predictive maintenance programs (experience)
- Knowledge of aircraft health monitoring systems (AHMS) and prognostics & health management frameworks (experience)
- Knowledge in CBM (Condition-Based Maintenance) (experience)
- Familiarity with ARINC, AFDX and ATA standards for aircraft data exchange (experience)
- Experience integrating AI models with maintenance information systems (MIS) or enterprise asset management (EAM) platforms (experience)
- Data analytics: data cleaning, manipulation and processing. Descriptive, diagnostic, predictive and prescriptive analytics focused on aircraft systems, using techniques for pattern recognition, data mining, design of experiments, etc. (experience)
- Knowledge of AI techniques or development of complex algorithms focused on time series, NLP and image processing (experience)
- Programming knowledge: advanced level of Python and its main libraries dedicated to analytics and data science such as Pandas, Numpy, Matplotlib, Seaborn, Bokeh, Scipy, Scikit-learn, Tensorflow, Keras, NLTK, SQLAlchemy (experience)
- Knowledge in handling tools dedicated to data visualization such as Spotfire, Tableau, PowerBI (experience)
- Knowledge in the development of queries for the extraction and manipulation of data: SQL (experience)
- Basic knowledge of relational and non-relational databases (experience)
- Knowledge of GIT, version control and collaborative development (experience)
- General knowledge of the complete V&V development cycle (experience)
Responsibilities
- Drive the design, develop and deploy predictive maintenance models to anticipate aircraft component failures and optimize maintenance schedules
- Establish and maintain data integrity requirements to ensure the data set needed to feed the predictive maintenance models
- Participate in defining the certification basis for CBM applications ensuring compliance with aviation authorities and alignment with safety and reliability objectives
- Integrate and analyze flight data, health monitoring system (HMS) outputs, sensor data, and maintenance logs
- Collaborate with avionics, propulsion, and airframe engineering teams to interpret system behaviors and identify degradation patterns
- Develop dashboards, KPIs, and data pipelines for real-time maintenance insights
- Implement data preprocessing, feature engineering, and anomaly detection methods
- Lead the validation and continuous improvement of predictive algorithms in operational environments
- Support digital twin and reliability-centered maintenance (RCM) initiatives
- Ensure compliance with aviation standards in predictive maintenance applications
- Communicate technical findings to non-technical stakeholders through clear visualizations and reports
- Analysis of the aircraft problems also from a Systems Engineering point of view: it is important to understand the operation of the system and the possible contributions to system failures
- Documentation, preparation and exposition of presentations to show and communicate the model development process and the results obtained graphically and visually
Benefits
- general: Flexible working arrangements to stimulate innovative thinking
- general: Commitment to workforce diversity and inclusive working environment
- general: Equal opportunities for all
Tags & Categories
Answer 10 quick questions to check your fit for Predictive Maintenance & Analytics Transformation Specialist @ Airbus.
Related Books and Jobs