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Ownership of Data Assets & strategy: Own pre-training, evaluation, and meta-data including proprietary, open-source, and synthetic datasets. Develop and execute vision....

• Implementation and support of VB.NET based software solution
• Participation in the run and maintain team for MES software

• Build Data Pipelines: Design, build, and maintain scalable data pipelines for ingesting, transforming, and serving financial and operational data.
• Work with ERP Data: Integrate and model data from ERP systems and finance tools, including accounting, controlling, procurement, revenue, and cost data.

• Define and execute the reporting and analytics transformation roadmap (towards lean target setup)
• Establish a scalable target architecture from data source through modelling and semantic layer to reporting frontend

Focus on the medical applications of our ORBIS hospital information system, you will be responsible for customised configuration using our development tools (ORBIS Form Designer, ORBIS Medical Query Generator, ORBIS Experter, Jaspersoft® Studio, ORBIS U-Composer)...

Where you belong: Where you belong: ...

• Define and evolve data models for R&D entities
• Design and implement robust data pipelines and automated data quality checks
• Improve traceability and metadata management so data can be understood, trusted, and reused across teams

• Investigate and resolve data inconsistencies across complex end-to-end data pipelines
• Automate complex analytics across large datasets to validate outputs and identify anomalies or inconsistencies
• Debug pipeline failures and improve overall pipeline robustness

Manipulating and analyzing complex, high-volume and high-dimensional data to gain insights by using appropriate data analysis techniques, algorithms and programming languages in close collaboration with subject matter experts...

As a Machine Learning Engineer in our Retail ML team, you will take end‑to‑end ownership of designing, developing and maintaining advanced machine learning solutions that directly influence our commercial performance. Your work will span dynamic pricing, demand forecasting and data‑driven buying...

• Keep data moving: Build, run, and refine data pipelines and workflows (Python, Airflow/Cloud Composer) so they're reliable, fast, and easy to change
• Shape our data models: Use BigQueryand Cloud Spanner to design wellstructured, highperformance datasets for analytics and machinelearning use cases

You provide technical and disciplinary leadership for an architecture team of around 10 software and security architects, including senior subject-matter experts (databases, performance, security, cloud, and integration), and you grow, align, and deploy them where they have maximum impact....

Own SEO data pipelines end-to-end. Design, build, and maintain automated pipelines that power all SEO analytics, from ingestion through transformation to dashboarding....

• Partner with internal teams and model researchers to evaluate high-value use cases and understand their business context.
• Analyze use cases across the organization and advise on how to make them work effectively with our tabular foundation models.

• WinningTeam – You are part of a highly skilled and motivated project team and you are eager to contribute to the project success
• GettingToKnow about the Zone Architecture
• LearningAbout different Testing tools used in Automotive

You understand our platform architecture, existing systems and tech stack (C#/.NET, MongoDB, Docker, Kubernetes, GCP/Azure) deeply enough to independently plan and ship features....

• Develop both classical algorithms and modern machine learning techniques
• Implement algorithms efficiently on embedded hardware
• Optimize parameters for complex, hybrid image pipelines
• Develop innovative solutions for hardware-constrained challenges

• Designing and implementing end-to-end data flows from device data ingestion through transformation, storage and consumption
• Defining data models, structures and lifecycle concepts to ensure data quality, consistency and lineage

• Make optimization runs fast enough that customers iterate in minutes, not hours — across problems an order of magnitude larger than today
• Build the data backbone: ingest SAP/ERP exports, Excel reality, and operator knowledge into a clean, versioned, traceable model layer

• 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.