Junior data analyst állások Németországban (programozó, fejlesztő)

• Design, and manage deployments on Kubernetes clusters within our internal and commercial cloud infrastructure
• Develop and maintain state-of-the-art/modern FastAPI-based microservices, ensuring automated and reliable deployment using Helm charts and Pulumi

• Unique opportunity to contribute to the development of the SAP-RPT model family
• Design, develop and manage tools and data pipelines that enable the processing of tabular data at scale

to generate and harmonize user-friendly, standardized data analysis pipelines for a variety of computational tasks, including, but not limited to, mutation calling, bulk and single-cell RNA-seq analysis, ChIP-seq / Cut&Run analysis, CRISPR screen analysis, and DNA barcoding analysis,...

• Develop and maintain ETL/ELT pipelines for both structured and unstructured data
• Ensure the integrity, availability, and performance of data across ingestion and storage layers
• Collaborate with analysts and architects to translate business requirements into scalable data models

You design and build high-performance search and query pipelines over PB-scale MDF4 and MCAP data lakes, enabling ML engineers to find relevant driving scenarios, sensor conditions, and edge cases across billions of records in seconds....

• You advise and support business units throughout their digital transformation journey and identify automation potential.
• You develop and implement automation solutions based on UiPath.
• You design and realize agentic AI solutions that independently analyze processes, make decisions, and act.

• You will contribute to improving our foundation recommender system
• Your role involves exploring and evaluating new machine learning methods, including applications of LLMs for recommender systems
• Expect to support personalized CRM communications (push notifications, in-app messages, newsletters)

Where you belong: Where you belong: ...

Where you belong: Where you belong: ...

• Become familiar with our previously developed neural network superstructure for learning iterative algorithms
• Extend the superstructure to tackle AC-PF problems of different complexities and assess its convergence in inference
• Investigate scaling and performance bottlenecks

• development of computational methods and processing pipelines for large image datasets
• application of existing and development of new analytical and ML solutions
• data visualization and communication
• work in close collaboration with our medical collaboration partners