Senior Data Scientist

The Senior Data Scientist is responsible for the development and deployment of predictive models, transforming complex data into scalable, high-impact analytical solutions. Main Accountabilities Minimum 4 years of hands-on experience in Data Science, ΑΙ, Machine Learning or Advanced Analytics. Proven experience designing and implementing end-to-end data science solutions for complex business problems. Demonstrated experience taking solutions from proof of concept to production, including testing, packaging, deployment, monitoring and continuous improvement. Strong hands-on programming experience in Python, including object-oriented programming, modular code design, exception handling, logging, unit testing and development of reusable, maintainable and production-ready solutions. Hands-on experience with Databricks, Apache Spark and PySpark for large-scale data processing, analytics and development of scalable solutions. Experience with Git-based development, version control, code reviews, CI/CD practices, model deployment, monitoring and lifecycle management. Advanced knowledge of SQL and experience working with large and complex datasets, including data extraction, transformation, validation and query optimization. Familiarity with AWS cloud environments and services supporting data storage, processing and application integration will be considered an advantage. Strong knowledge of machine learning and data science libraries, including pandas, NumPy, scikit-learn and MLflow. Education, Experience and Technical Skills Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, Mathematics or another quantitative discipline. Minimum 4 years of hands-on experience in Data Science, ΑΙ, Machine Learning or Advanced Analytics. Proven experience designing and implementing end-to-end data science solutions for complex business problems. Demonstrated experience taking solutions from proof of concept to production, including testing, packaging, deployment, monitoring and continuous improvement. Strong hands-on programming experience in Python, including object-oriented programming, modular code design, exception handling, logging, unit testing and development of reusable, maintainable and production-ready solutions. Advanced knowledge of SQL and experience working with large and complex datasets, including data extraction, transformation, validation and query optimization. Hands-on experience with Databricks, Apache Spark and PySpark for large-scale data processing, analytics and development of scalable solutions. Familiarity with AWS cloud environments and services supporting data storage, processing and application integration will be considered an advantage. Strong knowledge of machine learning and data science libraries, including pandas, NumPy, scikit-learn and MLflow. Experience with Git-based development, version control, code reviews, CI/CD practices, model deployment, monitoring and lifecycle management. Competencies Ownership and accountability, responsibility for decisions and commitment to results Adaptability and innovation, openness to change and continuous learning Customer focus, understanding needs and building strong relationships Proactivity and initiative, problem solving and opportunity identification Professional ethos, alignment with values and compliance standards Collaboration, teamwork and effective stakeholder relationships Business and strategic thinking, growth opportunities and long-term planning Leadership, role modeling, high standards and performance recognition