We’re looking for a Senior Applied Data Scientist with a strong background in machine learning and data engineering to join a long-term initiative within the financial sector. You’ll work on cutting-edge projects focused on anti-money laundering (AML) and transaction monitoring, supporting one of Europe’s leading banking groups.

This is a fully remote, EU-based opportunity, with high-impact, cross-country deployments in the banking ecosystem.

What You'll Do

Build and optimize machine learning models for transaction monitoring, anomaly detection, and customer segmentation.
Analyze complex financial transaction datasets across 30+ international subsidiaries.
Collaborate with domain experts to implement statistical models that detect financial crime patterns.
Develop scalable pipelines for model training and data transformation (Python, Spark).
Work hands-on with Git-based workflows, cloud environments, and modern MLOps tools.
Contribute to an 18–24 month project with long-term potential and innovation at its core.

What We’re Looking For

10+ years of experience in data science, applied machine learning, or related fields (data mining, statistical modeling, etc.)
Strong understanding of classification, clustering, and anomaly detection algorithms
Experience working with financial datasets or in banking/anti-financial crime domains
Hands-on experience with Python, Spark, Git, and ML libraries (e.g., Scikit-learn)
Proficiency in building scalable data workflows and collaborating in distributed teams
Excellent English communication skills (written & verbal)
Based in the European Union (required for compliance & remote setup)

Nice to Have