GenAI Data Scientist

Main tasks

• Contribute to AI and Data Science projects focused on Natural Language Processing (NLP), Generative AI (GenAI), and core Data Science activities
• Lead and contribute to end-to-end Data Science and Machine Learning initiatives, from data understanding and preparation to modelling, evaluation, and deployment
• Perform exploratory data analysis (EDA) to identify patterns, insights, and opportunities for model development
• Develop, train, evaluate, and optimize Machine Learning models using Python and industry-standard frameworks
• Prepare and transform data using tools and technologies such as SQL and pandas
• Develop and implement Generative AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and prompt engineering
• Work with cloud infrastructure to support Data Science and Machine Learning solutions
• Apply software engineering best practices to ensure code quality, maintainability, and reliable delivery

Requirements

• Minimum of 5 years of professional experience in Data Science and Machine Learning projects
• Proven experience delivering end-to-end Data Science and Machine Learning initiatives
• Strong knowledge of Data Science principles, particularly exploratory data analysis, modelling, and evaluation
• Strong Python skills and professional experience with Data Science and Machine Learning frameworks such as scikit-learn, PyTorch, Keras, OpenCV, and pandas
• Experience with data preparation and transformation using SQL and pandas
• Professional experience with cloud infrastructure, with AWS highly preferred
• Experience with LLMs, RAG, prompt engineering, and Generative AI technologies, such as OpenAI and Amazon Bedrock
• Fluent English, written and spoken, at CEFR C2 level

Nice to have

• Professional experience with MLOps solutions such as MLflow and Databricks
• Experience with software engineering best practices and tools, including Git, CI/CD pipelines, and unit testing

Other requirements

• Fluent in English
• Ability to simplify complex problems and obtain a workable solution;
• Customer focus and service delivery;
• Availability to work in EU.