Data Scientist GenAI & Machine Learning

Responsibilities

• Development and implementation of modern data science and machine learning solutions for complex business and process-related questions.
• Conception, setup, and optimization of Generative AI use cases based on current Large Language Models (LLMs).
• Development of Proof of Concepts (PoCs) for validating innovative AI applications.
• Analysis and preparation of unstructured and semi-structured data for use in AI and machine learning models.
• Conception and optimization of RAG (Retrieval Augmented Generation) architectures, including chunking, retrieval, and prompting strategies.
• Setup and further development of evaluation frameworks for LLM, RAG, and agent systems.
• Development of statistical models and machine learning algorithms for Predictive AI use cases.
• Close collaboration with business departments, data engineers, and other stakeholders to develop data-driven solutions.

Requirements

Particularly Desirable

• Successfully completed studies in Computer Science, Mathematics, Statistics, Physics, Data Science, or a comparable field.
• Several years of experience as a Data Scientist, Machine Learning Engineer, or AI Engineer.
• Very good knowledge in the areas of Machine Learning, Statistics, and Data Science.
• Sound practical experience with Python as well as common data science frameworks such as Pandas, NumPy, Polars, Scikit-Learn, PyTorch, or TensorFlow.
• In-depth understanding of Large Language Models (LLMs), Generative AI, and modern AI architectures.
• Experience with RAG systems, prompt engineering, and document analysis.
• Knowledge in the development and execution of evaluations for AI systems, for example with Ragas, DeepEval, or Langfuse.
• Experience in handling NLP methods and processing large amounts of data.
• Analytical mindset as well as the ability to communicate complex issues understandably.
• Experience in the banking or financial sector.
• Knowledge of Dataiku DSS or comparable data science platforms.
• Experience with agent systems and the evaluation of AI-supported assistance systems.
• Know-how in the area of predictive analytics and time-series modeling.

Project details

• Start: ab sofort
• Duration: 14 Monate
• Remote: remote
• Location: Frankfurt a. Main, Deutschland, DE
• Languages: German