Senior Data Scientist

Titan Group is seeking a Senior Data Scientist to join the Group Digital Solutions team, which designs, builds, and supports digital and AI-powered tools driving Titan’s transformation in Supply Chain and Customer Experience.

In this role, you will collaborate daily with data scientists, data engineers, software engineers, DevOps specialists, and Supply Chain experts to deliver advanced digital products that enhance Titan’s operating model.

Responsibilities

• Design and develop ML- and optimization-driven applications that support and enhance Supply Chain operations.
• Drive end-to-end delivery of Supply Chain use cases, deploying scalable forecasting, planning, scheduling, and logistics optimization tools.
• Participate in the full lifecycle of new tools-development, deployment, monitoring, maintenance, and continuous improvement.
• Build monitoring and performance-evaluation capabilities to ensure reliability and accuracy of deployed models and optimization engines.

• MSc in Computer Science, Data Science, Engineering, or a related STEM field.
• Minimum 5 years of experience delivering production-grade analytics solutions (forecasting, optimization, or advanced ML).
• A mindset of ownership, strong communication, desire to learn from the domain experts, and a drive for continuous improvement, with proven experience in structuring projects and guiding small workstreams.
• Ability to work with diverse cross-functional teams, influencing without direct authority to drive alignment and adoption of tools.
• Strong programming skills in Python (including OOP), Git, and SQL.
• Hands-on experience in software development practices, as well as MLOps/DevOps in production environments.
• Excellent command of Greek and English, both written and verbal.
• Military obligations completed (if applicable).

Bonus if you have

• PhD in a data, analytics, or computational field.
• Background in Operational Research or experience with Supply Chain optimization algorithms.
• Familiarity with Azure, Docker, containerization, and CI/CD pipelines.
• Experience with advanced ML techniques such as Deep Learning or Reinforcement Learning.
• Self-motivated exploration of new development paradigms, such as agentic workflows and vibe-coding techniques.