Senior Data Scientist - Gen AI - Finance (h/f) (IT)

Vous êtes un Data Scientist expérimenté, spécialisé dans l'IA générique et Python ? Emagine vous offre l'opportunité de guider et de diriger le développement de structures et d'outils efficaces afin de créer des applications d'IA fiables et dignes de confiance dans un environnement bancaire international. Are you an experienced Data Scientist with expertise in Gen AI and Python?Emagine has an opportunity for you to guide and lead the development of effective structures and tools to create reliable, trustworthy AI applications within a global banking environment. As part of an AI-focused emagine team working on Gen AI initiatives that leverage LLMs and advanced techniques to solve complex business problems. You will work on unstructured data from sources such as legal documents and financial trading policies, building solutions that enable accurate and reliable outcomes. Main ResponsibilitiesLead the design and implementation of Gen AI solutions for text-based and LLM-driven use cases. Develop Python-based tools for data ingestion, modelling, and manipulation of large volumes of unstructured data. Define effective structures and frameworks to ensure reliability and trustworthiness in AI applications. Collaborate with legal and compliance teams to process and model complex datasets. Key Requirements5+ years of experience in Data Science including international corporate environments. Strong expertise in Python and hands-on experience with LLMs (e.g., Lama 7DB, GPT-4 API). Familiarity with vectorization, chunking, and advanced data modelling techniques. Knowledge of tools such as PySpark, MongoDB, graph databases, SparkleDP. Self-driven, proactive, and comfortable working in a fast-paced environment. Nice to HaveExposure to legal or procedure-focused applications. Other DetailsWork is a minimum of 3 days per week on-site (8th). Apply with your latest CV or reach out to Brendan to find out more. Profil candidat: Plus de 5 ans d'expérience dans le domaine de la science des données, y compris dans des environnements d'entreprise internationaux. Solide expertise en Python et expérience pratique des LLM (par exemple, Lama 7DB, GPT-4 API). Connaissance de la vectorisation, du chunking et des techniques avancées de modélisation des données. Connaissance d'outils tels que PySpark, MongoDB, les bases de données graphiques, SparkleDP. Autonome, proactif et à l'aise dans un environnement dynamique.