Senior Data Scientist

Il y a 3 jours

Arrondissement of BrusselsCapital, Brussels, Belgique NEBIRU Temps plein

Looking to start a new challenge as a freelancer? Get in touch now.

What you will do

  • Develop and continuously improve fraud detection models using machine learning, anomaly detection, graph analytics and behavioural analytics.
  • Transform large-scale transactional and customer data into actionable fraud intelligence.
  • Lead feature engineering, data enrichment, data quality and dataset preparation for fraud analytics.
  • Analyse complex fraud patterns, emerging attack vectors and suspicious networks to identify new detection opportunities.
  • Design analytical solutions that can operate reliably at scale and contribute to production AI applications.
  • Partner with Fraud Operations, Risk, Compliance and Product stakeholders to translate business challenges into effective data-driven solutions.
  • Investigate model performance and continuously improve detection accuracy while considering operational impact and business value.
  • Contribute to the evolution of fraud analytics practices, methodologies and technical standards.

What you bring

  • 7+ years of professional Data Science experience, with significant experience in fraud detection, fraud analytics or a closely related domain.
  • Strong hands‑on Python and SQL skills, including experience with Pandas and large-scale data processing.
  • Proven experience working with Spark or other distributed data‑processing technologies.
  • Strong knowledge of supervised and unsupervised machine learning, anomaly detection and predictive modelling.
  • Practical experience with graph analytics, network analysis or behavioural analytics applied to fraud or risk problems.
  • Demonstrated ability to turn complex, high-volume data into robust analytical and ML solutions.
  • Experience taking data science solutions towards production, working with software engineering and/or ML engineering teams.
  • A proactive, autonomous and business-oriented approach.