We are looking for a
Data Engineer
to join a strategic technology transformation project in the financial sector. The goal is to modernize the data architecture and enhance digital and AI capabilities for risk prevention and financial crime detection.
Key Responsibilities Design and optimize data pipelines ensuring quality, traceability, and compliance with privacy and security regulations. Collaborate on the implementation and evaluation of AI-based and automation solutions. Integrate tools for model performance monitoring and tracking. Work closely with validation experts to operationalize model governance processes.
Required Profile Proven experience in data engineering and pipeline development in complex environments. Proficiency with tools for analysis and modeling (e.g.,
Jupyter Notebook, Python). Familiarity with AI/ML-oriented architectures and model validation practices. Ability to work on projects requiring regulatory compliance and high-quality standards.
Technologies & Approach Use of environments such as
Jupyter Notebook
for feature creation. Integration with specialized platforms for anomaly detection and fraud prevention (e.g., solutions like
ThetaRay ). Hybrid models: unsupervised algorithms for feature generation and supervised algorithms for triage processes.
Preferred Qualifications Experience in projects related to fraud prevention, Financial Crime Compliance, or risk management. Knowledge of emerging technologies: Machine Learning, NLP, process automation. Advanced English for collaboration in international environments.