About the team you are joining The Global Aviation Data Management (GADM) team is responsible for the development, implementation and support of data solutions needed to monitor safety, operational and capacity KPIs. These include: Managing Safety and Operations Data Sharing Programs Supporting OSS lines of business in their data, analytics, reporting and dashboard needs Developing a coherent approach to data visualization and analysis Ensuring the availability, reliability, and quality of the data and related dashboards through continuous monitoring Adhering to data governance policies, quality standards and best practicesText What your day would be like Reporting to the Director, OSS Business Systems and Performance, you will drive innovation through advanced analytics, data science, and AI. Leading a team of data specialists, you will advance analytical capabilities, oversee data integration and quality across diverse datasets, and deliver value-added solutions that identify emerging safety and security risks, operational trends, and opportunities. What your day would be like Lead, inspire, and develop a high‑performing team of data specialists, analytics professionals and data scientists. Set and execute the OSS vision and strategy for data insights and advanced analytics aligned with the corporate guidelines. Oversee data integration across internal and external sources, ensuring scalable, reliable, and timely data pipelines for GADM and OSS Shape and execute a data strategy that transforms complex industry data into actionable insights, enabling better decisions and measurable outcomes. Partner closely with internal and external stakeholders to translate strategic priorities into analytical use cases, models, and insights. Build collaborative relationships with IT technology peers to ensure solutions alignment with the enterprise architecture principles and technological building blocks. Establish and enforce data quality, governance, and metadata processes to ensure trusted, accurate, and business‑ready data. Define and track KPIs and outcomes to measure the impact, effectiveness, and ROI of analytics and AI initiatives. Promote a data‑driven culture by enabling self‑service analytics, upskilling teams, and improving data literacy across the organization. Continuously evolve data and analytics capabilities by evaluating emerging technologies, techniques, and best practices and champion the adoption of modern analytics platforms, cloud technologies, and AI/ML capabilities in collaboration with IT peers. Ensure responsible and ethical use of data and AI, including compliance with regulatory, privacy, and security requirements.