Job Description:

Airbus is an international pioneer in the aerospace industry. We are a leader in designing, manufacturing and delivering aerospace products, services and solutions to customers on a global scale. We aim for a better-connected, safer and more prosperous world.

A commercial aircraft manufacturer, with Space and Defense as well as Helicopters Divisions, Airbus is the largest aeronautics and space company in Europe and a worldwide leader. 

Airbus has built on its strong European heritage to become truly international – with roughly 180 locations and 12,000 direct suppliers globally. The company has aircraft and helicopter final assembly lines across Asia, Europe and the Americas, and has achieved a more than sixfold order book increase since 2000.

Description:

Digital Workplace (DW) was established to be an enabler of Digital Transformation across Airbus. Its primary focus is to: provide employees with simple, intuitive and easy to use workplace tools and services; enable employees to create and collaborate from anywhere at any time; enable continuous optimisation of work experience and productivity underpinned by fit-for-purpose security. 
Digital Workplace consists of the following core elements: Operational Performance, Devices and Services, Employee Collaboration, Industrial and Specialist Devices, Workplace Support, User Adoption.

We are currently looking for a new colleague mastering data analysis and tooling to join the Operational Performance PSL (DWW). His/Her expertise will support us to bring data to life. Thus we will make the right decisions in the product design and at project steering and also we will have all the information required to transform and to improve user experience.

Position Summary:

The Data Analyst will play a key role in designing, developing, and deploying scalable data solutions within the Skywise / Palantir Foundry platform or other equivalent platforms to support Airbus divisions and functions across Europe. This position combines strong analytical, technical, and communication skills to drive business value through data insights and automation. This position bridges quantitative data analysis, software engineering, and applied artificial intelligence to transform operational datasets into proactive, actionable insights and automated enterprise solutions. Operating within the Skywise / Palantir Foundry framework, Cloud environments (AWS/GCP), and ServiceNow, you will architect, build, and deploy production-grade predictive algorithms, machine learning models, Generative AI capabilities, and interactive operational tools to empower business decision-making across Airbus divisions globally.

The specialist will work closely with business and technical teams to identify opportunities for improvement through data value analysis, develop end-to-end analytics solutions, and promote data-driven decision-making across the organization.

Qualification & Experience:

We seek out curious minds. We value attention to detail, and we care deeply about outcomes. We are looking above all for passionate people, eager to learn, willing to share, establishing innovative ways of working and influencing culture change.  

Are you ready to share this exciting challenge with us? 

• Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Artificial Intelligence, Applied Mathematics, Statistics, or a related quantitative field.
• Experience: 4 to 7 years of hands-on experience in building, deploying, and scaling end-to-end data pipelines, predictive models, machine learning solutions, and software automation systems.
• Certifications: At least one recognized cloud or AI certification (e.g., Google Cloud Professional Machine Learning Engineer, AWS Certified AI/ML Specialist, or equivalent credentials).
• Platform Expertise: Proven track record using Skywise / Palantir Foundry, AWS/GCP cloud platforms, and ServiceNow operational environments.
• Proven track record in developing and maintaining large-scale data applications on Foundry. Proficiency in Ontology Manager, Code Authoring, Contour, Workshop, and Data Ingestion modules. Experience in  ETL scripting for data transformation.
• Advanced proficiency in Python, SQL, React, JavaScript, and CSS. and strong understanding of REST APIs andBig Data architectures.
• Advanced analytical expertise in data modeling, database management, and SQL (expert level).
• Experience with BI tools, Google Data Studio, and BigQuery.
• Proficient in data acquisition, automation, and maintaining data systems from multiple sources.
• Ability to identify valuable data sources and optimize data collection processes and Strong analytical mindset with exceptional attention to detail and accuracy.
• Ability to help transform organizational reporting processes through automation and optimization.

Key Requirements and Responsibilities:

• End-to-End AI & Data Engineering: Design, build, evaluate, and deploy production-grade ML models and statistical solutions in Skywise/Foundry and Cloud platforms to transition from descriptive reporting to predictive/proactive analytics.
• Develop, test, document, and deploy data pipelines, analytical models, and visualization tools to support strategic and operational initiatives.
• Work with Product Owners and core Airbus business functions to capture requirements, understand business processes, and deliver impactful data-driven solutions.
• Manage the full application delivery lifecycle — from design and implementation to testing, deployment, and support.
• Build and maintain pipelines to enable automated deployments across Development, QA, and Production environments.
• Troubleshoot and resolve application issues, manage incidents and requests, and provide ongoing support for developed tools.
• Encourage and enable self-service analytics by empowering business teams and promoting data literacy.
• Coach and develop data analytics awareness among internal customers and stakeholders.
• Define, implement, and maintain KPI metric reports, dashboards, and performance analytics (PA) reporting.
• Help automate reporting processes and transform the organization’s approach to data management.
• Acquire data from various sources, manage and maintain data systems, and automate data collection processes.
• Ensure compliance with best practices in data quality, security, and governance.
• Behavioral Analytics & Anomaly Detection: Build behavioral engines to identify operational leakages (e.g., ghost asset detection, hardware failure modeling, supplier CMDB update lag, and usage anomalies).
• Intelligent Automation & Modernization: Design intelligent workflows, self-healing data scripts, and RAG-driven knowledge tools to automate domain-specific tasks and optimize IT Service Management processes.
• Pipeline & Feature Store Management: Feature-engineer unstructured datasets from ServiceNow, telemetry (Workblaze/DEX), and enterprise systems into robust data pipelines across Dev/QA/Prod environments.
• Governance & FinOps: Ensure compliance with Airbus data governance, privacy, security frameworks, and ethical AI standards while tracking model inference costs and API spend.

Technical Essentials:

• Programming & Data Wrangling: Mastery of Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow) and expert-level SQL for querying and transforming large-scale datasets.
• Cloud & Platform Ecosystems: Deep proficiency in Skywise / Palantir Foundry (Ontology, Workshop, Contour) and Google Cloud Platform (Vertex AI, BigQuery, Cloud Run) or AWS (SageMaker, Bedrock, Lambda).
• Generative AI & Advanced ML: Experience with RAG architectures, vector databases (Pinecone, ChromaDB, Vertex Vector Search), LLM frameworks (LangChain/LlamaIndex), and core ML algorithms (Regression, Classification, Time-Series Forecasting).
• MLOps & DevOps: Hands-on experience with REST APIs, Docker, Kubernetes, CI/CD pipelines, and automated model deployment/monitoring workflows.
• BI & Visualization: Proficiency in Qliksense, Looker Studio, Workshop, or Performance Analytics dashboards to present predictive insights to stakeholders.
   

Soft Skills & Behavioural Attributes:

• Strategic Mindset & ROI Focus: Ability to translate complex business problems into viable AI use cases with tangible ROI and operational impact.
• Communication & Storytelling: Exceptional skills in explaining complex machine learning models, statistical findings, and predictions to non-technical business leaders.
• Adaptability & Problem-Solving: Thrives in dynamic environments, demonstrates strong curiosity, attention to detail, and a passion for continuous learning.
• Cross-Functional Collaboration: Ability to work effectively with Product Owners, Agile delivery teams, L1/L2 support units, and European leadership.

Good to Have:

• Familiarity with Digital Employee Experience (DEX) metrics and telemetry tools (Workblaze / Nexthink).
• Exposure to source-to-source code parsing, AST analysis, or automated design document generation utilities.
• Experience with ITIL frameworks, SAFe / Agile Scrum delivery methodologies, or ServiceNow portal development.
• Fluency or working proficiency in French or German in addition to mandatory English fluency.
• Coach internal business users with a goal of being largely self-sufficient for their analytics needs
• Research and document new and improved features on existing tools 
• Become familiar with new analytics technologies in Airbus and in the marketplace
• Stay current on latest analytics trends and emerging technologies 
• Recommend new ways of using tools to further business needs

• User experience oriented

• Fluency in English is mandatory, French or German knowledge will be an added advantage 

• Working experience in Agile Scrum, SAFe and/or Kanban projects

Success Metrics

Success will be measured in a variety of areas, including but not limited to

• Model Accuracy & Deployment: Successful high-accuracy deployment and adoption of predictive models in production with low latency and high uptime.
• Operational & Cost Impact: Measurable cost savings and waste reduction via operational anomaly identification and SLA breach prevention.
• On-Time Quality Delivery: Consistently delivering first-time-right AI/ML initiatives throughout the complete lifecycle.
• Stakeholder Satisfaction: Satisfaction scores and strong collaboration feedback across Airbus Digital Workplace leadership and European product units.
• Bring innovative cost effective solutions
• Achieve the customer satisfaction
• Ability to handle a subject from demand management, to development and support
• Ability to understand the business potential of applications and provide insight to clients

The role will also have the following key outputs:

• Strong link with all the Airbus Digital Workplace services
• Proactive in providing guidance & inputs for the Airbus Digital Workplace strategic roadmap

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.

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.

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