Data Scientist / MLOps Engineer

We are currently looking for a Data Scientist / ML Ops Engineer to join a strategic global banking initiative focused on building, deploying and scaling machine learning solutions in production environments. The role sits at the intersection of data science and engineering, with strong ownership of end-to-end ML pipelines and operational excellence.

You will work within a cross-functional, international team of data scientists, ML engineers, software engineers and cloud specialists, contributing to enterprise-scale analytics and AI platforms used across the organization.

• Strong Python skills (Pandas, Scikit-learn, TensorFlow or similar).
• Experience in building and maintaining data pipelines.
• Hands-on experience with ML Ops practices: CI/CD, monitoring, versioning.
• Experience with AWS and cloud-based ML solutions.
• Solid background in data analysis and data visualization.
• Ability to work effectively in cross-functional engineering teams.

• Design, develop and maintain end-to-end data and ML pipelines.
• Build, train and evaluate machine learning models using Python and modern ML frameworks.
• Implement ML CI/CD processes, model versioning and automated deployments.
• Monitor models in production (performance, drift, reliability) and ensure their stability.
• Collaborate closely with engineering, platform and business teams to deliver scalable ML solutions.
• Contribute to cloud-based ML architectures and best practices.