3 data analytics jobs found in Munich

YOUR TASKS You will support the integration of (generative) AI technologies into existing application software or develop new, innovative solutions with AI components together with the team. You will assist in the analysis and preparation of data specifically for (generative) AI use cases. You will support the evaluation and optimization of software with AI components, especially with frameworks like LangChain, as well as through the use of APIs like OpenAI or Ollama. You will provide support in cloud-native development projects with a focus on AI-powered software solutions. You will support the integration and use of AI-compatible database systems (e.g., relational, vector, or graph databases) for AI applications. You research new technologies and methods in the field of (generative) AI (e.g., ModelContextProtocol, agent technologies and modern AI integration frameworks). YOUR PROFILE You are enrolled in a degree program with AI content and have a...

Join the Cavalis team At cavalis, we believe the next generation of consulting is hands-on, data-driven and powered by AI. We are looking for Forward Deployed AI Engineers who combine skills in data science, machine learning and process analytics to deliver measurable business impact. In this role, you will work directly with our clients, from scoping challenges to building and deploying solutions in their environments. You will implement advanced analytics and AI use cases, and you will ensure that our clients unlock the full potential of their data and processes. Why Cavalis Be part of a growing consultancy where your work makes a visible difference Work on projects that span process mining, advanced analytics and AI/ML – sometimes combined, sometimes standalone. Develop and deploy real solutions with SQL, Python and AI frameworks inside customer environments. Work closely with clients, from operational teams to senior executives. Grow continuously through...

Your tasks: Data Architecture & Integration:   Development, implementation & further development of scalable data concepts and architectures (e.g., Data Lakehouse) for data integration as well as implementation of BI & Advanced Analytics. Lifecycle support & strategy implementation:   Supporting the platform manager throughout the entire lifecycle and advising on the implementation of data & AI strategies. Data landscapes & use cases:   Reviewing data sources, quality & suitability for use cases, identifying potential value enhancements and end-to-end project management of data & AI use cases. Process basis & automation:   Documentation of processes and identifying and developing optimizations through automation & AI Standards & Reuse:   Maintenance, implementation and improvement of reusable standards & projects in the data & AI field Technologies, Partners & Compliance:   Selection support,...