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2 data scientist position jobs found in Berlin

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Biostatistics Berlin data scientist position
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Full time  (2)
Deutsche Rentenversicherung Bund
07/03/2026
Full time
Data Scientist
Deutsche Rentenversicherung Bund Berlin, Germany
Location Berlin Remuneration Pay group 14 TV EntgO-DRV (64,939.90-92,560.73 euros) Entry date March 6, 2026 occupation Part-time (permanent), Full-time (permanent) Application deadline 03. April 2026 Tender number 11-026-2026 Tasks Responsible conceptualization, development and implementation of data science applications with a focus on GenAI and LLMs in cross-functional teams Performing complex modeling tasks in the field of machine learning (for example, Random Forest, Gradient Boosting) and in the context of Large Language Models (LLMs) and their fine-tuning. Visualizing and analyzing large datasets to detect bias or data drift and to ensure data quality Conception, development and validation of highly complex machine learning and statistical models for demanding applications Evaluation and implementation of new state-of-the-art algorithms and technologies, including deep learning...
Deutsche Rentenversicherung Bund
07/03/2026
Full time
Junior Data Scientist
Deutsche Rentenversicherung Bund Berlin, Germany
Location Berlin Remuneration Pay group 13 higher service TV EntgO-DRV (60,072.01-86,114.70 euros) Entry date As soon as possible occupation Part-time (permanent), Full-time (permanent) Application deadline 03. April 2026 Tender number 11-027-2026 Tasks Developing and evaluating metrics for quality assurance of generated responses in RAG systems Optimizing indexing and search strategies to improve the accuracy and efficiency of RAG applications Developing and implementing data science applications with a cross-functional team and/or external service providers. Performing complex modeling tasks in the field of machine learning (for example, Random Forest, Gradient Boosting, etc.) and in the context of GenAI (for example, Large Language Models, Fine-Tuning, etc.) Visualizing and analyzing large datasets, for example to detect bias or data drift; optimizing and maintaining semi-automated MLOps...
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