Data Scientist - Fraud - HQ Brussels

YOUR JOB IN A NUTSHELL

Join BNP Paribas Fortis' AI Tribe, a team of 90+ AI experts driving innovation across the bank through advanced analytics and Artificial Intelligence.

As a Data Scientist specialized in Fraud Detection, you will design and deploy cutting-edge AI solutions to combat evolving financial crime threats. Combining machine learning, graph analytics, and Generative AI, you will transform data into actionable intelligence that helps protect our customers, strengthen the bank's resilience, and shape the future of fraud prevention.

AND IN DETAIL

As a Data Scientist specialized in Fraud Detection, you'll design, build, and deploy AI solutions to help protect our bank and customers from evolving fraud threats. You'll work within our AI Tribe and collaborate with Fraud Operations, Risk, and Compliance teams to transform data into actionable fraud prevention and detection capabilities.

What You'll Do

• Develop and enhance fraud detection models using machine learning, anomaly detection, behavioral analytics, and graph analytics.
• Analyze large-scale transactional and behavioral data to uncover suspicious patterns and emerging fraud schemes.
• Engineer features, enrich datasets, and apply a data-centric and error-analysis approach to continuously improve model performance.
• Partner with cross-functional teams to translate business needs into scalable AI solutions.
• Investigate complex fraud cases, identify emerging attack vectors, and proactively mitigate risks.
• Leverage advanced AI techniques (traditional machine learning and also LLMs and Generative AI), to support fraud investigations and strengthen fraud prevention capabilities.
• Stay ahead of AI and fraud trends to continuously enhance our detection and prevention strategies.

YOUR TALENTS AND COMPETENCES

Education & Experience

• Master’s in Statistics, Computer Science, Data Science, or related field (PhD a plus).
• 3+ years in Data Science, preferably in financial services/fraud detection.
• Experience with fraud analytics, AML, or financial crime prevention.

Technical Skills

• Data-Centric AI & Data Engineering: Data collection, labeling, curation, enrichment, feature engineering, data quality, feedback, and large-scale data processing.
• AI & Fraud Analytics:
  • Machine Learning: Supervised and unsupervised learning for anomaly and fraud detection, model evaluation, performance monitoring, and error analysis.
  • Advanced Analytics: Graph analytics, network analytics, behavioral analytics, and financial crime analytics.
  • Generative AI & Foundation Models: LLMs, RAG, AI agents, deep learning , transactional model and AI-driven fraud prevention solutions.
• Programming & AI Engineering: Advanced Python, software engineering best practices, AI application development and deployment, monitoring, and end-to-end AI lifecycle management.

Soft Skills

• Analytical, proactive, and results-driven.
• Strong communicator who thrives in multidisciplinary teams.
• Comfortable in an international, fast-paced environment.

Languages

• Fluent English + Dutch or French (professional level).