Data Scientist

BNP Paribas Fortis is a leading bank based in Belgium that provides a comprehensive range of financial services to individual, corporate, and institutional clients. As part of the BNP Paribas Group, we benefit from the strength and stability of one of the world's largest banking networks. We offer a broad spectrum of products, including retail banking, wealth management, and investment solutions, while emphasizing digital innovation to enhance customer experience. We are committed to sustainable development and corporate social responsibility, aiming to support the economic growth and well-being of the communities we serve.

Mission: As part of the ongoing effort to modernize our software application landscape through application lifecycle management and Cloud migration, we face a significant challenge in constructing and valorizing a comprehensive knowledge base of our internal software. To this end, we have invested resources in developing a graph-based approach to knowledge management, resulting in a sizable knowledge graph that describes the structure of our codebase and interactions of various services, effectively creating a "Digital Twin" of our application environment.

Our goal is to exploit advanced graph-based methods (e.g. graph theory, graph learning/mining) to extract operationally and strategically valuable information from the knowledge graph.

Modernize the application management lifecycle and application migration management. Explore ways the existing knowledge graph can be valorized to reach the objective by leveraging advanced methodologies in graph theory, graph mining, and graph learning which go beyond what is generally found in the market as skill level.

Use cases:

• Extracting insights from the knowledge graph to improve the process of migration wave planning.
• Using information encoded in the digital twin to help migrate legacy applications to the new infrastructure.
• Fluency in Dutch or French.
• At least a Master’s degree in a quantitative discipline, such as statistics, mathematics, or engineering (a PhD is considered an advantage). Candidates with other academic backgrounds with substantial knowledge of analytics are also encouraged to apply.

Expectation: 50% on-site & 50% homeworking.

Experience:

Senior expert in data science with expertise in digital twins and graph-based approaches, who will ensure that the appropriate state-of-the-art technology is being used during the mission while supporting the Associate in their daily work.

Technical experience:

• AI - Machine Learning: R/Rstudio, SAS, LLMs, NLP, ASR, Graph learning.
• Programming languages: Python, Spark, Ansible scripts, SQL, Scala (optional), Kafka (optional), Flink (optional).
• Development Tools & Libraries: Conda, GitLab, Jupyter, PyCharm.
• Databases: SQL, Neo4j.

Join our team!

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