Join our high-impact AI team within BNP Paribas’s Corporate & Institutional Banking (CIB) division, where You’ll design, build, and deploy AI-powered solutions to revolutionize how we extract insights from unstructured data, automate decision-making, and enhance operational efficiency. Your work will directly impact credit risk assessment, client onboarding, and regulatory compliance - driving innovation at the heart of global banking.

As a team, we develop and scale a cutting-edge software platform powering the entire corporate credit chain - from origination to monitoring. Used by thousands of employees across 50+ countries since 2019, our platform is a critical backbone for global credit operations. 

We work in Agile/Scrum with monthly production deployments, fostering a culture of continuous innovation and collaboration. As part of a 200+ international team organized into cross-functional feature squads, you’ll have access to:

• Mentorship & knowledge-sharing from top-tier local and global experts.
• Career growth through hands-on work on AI-driven solutions with real-world impact.
• Scaling opportunities as we expand our AI team significantly in 2026.

Data Scientist

Requirements:

• 3-5 years of professional experience in Machine Learning / Natural Language Processing – hands on experience with data cleaning, normalization and transformation.
• Hands-on experience with GenerativeAI, knowledge of OpenAI API (experience with agentic frameworks is a plus).
• Knowledge of NLP libraries and Machine Learning / Deep Learning frameworks (PyTorch / scikit / etc.). Experience with model assessment.
• Proficiency in Python programming.
• Production-oriented mindset – knowledge of Docker (Kubernetes is a plus), MLOps, basic knowledge of CI/CD pipelines, unit testing.
• Strong curiosity and willingness to learn.
• Team player attitude.
• Proficient English (mandatory for documentation and team communication).

Responsibilities:

• Extract critical data from documents – design and implement cutting edge information extraction pipelines that turn unstructured PDFs, contracts, statements and other banking documents into structured, searchable data.
• Build and deploy agentic AI solutions – create autonomous assistants that can act on behalf of clients and internal users, streamlining processes and improving decision making.
• Work daily with large language models (LLMs) fine tune, prompt, and integrate LLMs into production workflows to deliver real time insights.
• Apply state of the art Natural Language Processing (NLP) – leverage advanced NLP techniques for text classification, language generation and entity recognition, boosting data quality and operational efficiency across the bank.