Data állások, munkák it programozás, fejlesztés területen

• Define target architectures and roadmaps across AI & Data platforms that are aligned with our customers' business, IT and security requirements
• Translate between the worlds of engineering, business, IT and operations, making sure everyone ends up with the same picture

Daten verstehen und Mehrwert schaffen: Sie analysieren Daten aus Produktions-, Qualitäts-, Engineering- und Business-Systemen, entwickeln Datenmodelle und identifizieren im Team Optimierungspotenziale, Trends und Zusammenhänge für datenbasierte Entscheidungen....

• Analysis of global service quality data including non-conformance costs, corrective and preventive actions, customer satisfaction, NPS, and audit findings
• Transformation of analysis into clear conclusions and prioritized recommendations for regions, central functions, and management

  (SENIOR) IT APPLICATION AND DATA MANAGER ABOUT KOREAN RE SWITZERLAND AG Korean Re Switzerland AG (rated 'A+' with a stable outlook by S&P) is a 100% subsidiary of Korean Re in Seoul, an international reinsurance group with more than USD 5.7 bn of gross written premium and a track-record of more...

• Data pipeline development
• Data integration
• Data warehousing
• Data modelling
• Data quality and governance
• Performance optimization
• Collaboration with data scientists and analysts
• Technology selection
• Security and compliance
• Monitoring and troubleshooting

Design and maintain scalable Lakehouse architectures and data pipelines using Azure Data Factory, Databricks, and Microsoft Fabric to support analytics and AI products....

• Experience in different data science topics
• Independent delivery of data science projects
• Engagement with clients to understand business objectives and translate them into technical requirements
• Leading pre-sales technical discussions

• Lead and coordinate the AI project portfolio in the Medium & Low-speed Division from ideation through implementation and post-review.
• Take ownership of key AI initiatives in the Medium & Low-speed Division, driving execution when needed, and ensuring alignment with strategic objectives.

• Management of the Global Travel Data & Systems roadmap delivery
• Operation, integration and continuous improvement of GT business systems including GTME, GT Power BPM and Vision
• Governance and operational management of Global Travel commercial data and business systems

• Ownership of end-to-end lifecycle of domain data products including design, development, operationalization, evolution, and retirement
• Leadership of technical delivery across data ingestion, pipelines, transformations, APIs, and data engineering processes within the domain

• Contribute to pioneering technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Execute scientific experiments on internal as well as public data.

• Building and maintaining dataset ingestion, cleaning, and versioning pipelines
• Designing and operating labeling workflows including quality control and inter-annotator agreement tracking
• Owning dataset testing including coverage analysis, class balance, leakage detection, and dataset documentation

• Work on design, coding, and quality assurance tasks related to strategic product capabilities
• Drive platform decisions that balance security, scalability, operability, and product evolution across current and future phases
• Development activities in ABAP and Java.

• Development of advanced AI solutions
• Collaboration across divisions to design, develop, and deploy machine learning models and AI applications
• Working with state-of-the-art AI technologies including generative AI, natural language processing, and computer vision

• Development and optimization of AI applications for production and development processes
• Analysis of large production, quality, and process datasets
• Creation of dashboards and data models for data-driven decision-making
• Development of machine learning models for quality improvement

• Data assets and strategy: Own pre-training, evaluation and metadata assets, shape their strategy and expand them with new data sources.
• Data roadmap and prioritization: Maintain the short- and long-term roadmap, manage the extraction backlog and coordinate dependencies.

• Drive pioneering technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Expand the horizon of what is possible by bringing together rich semantic context with large scale business data

• Contribute to pioneering technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Define the data, training, and experimentation environment to enable scalable access to data and compute.

• Pioneer technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Gain new insights by bringing together rich semantic context with large scale business data.

• Designing, implementing, testing, and optimizing reliable, efficient, and high-quality data pipelines
• Automating the extraction, loading and transformation of data from a wide variety of sources
• Developing solutions for the automated acquisition of data from source systems