The Senior Data Scientist is responsible for the development and deployment of predictive models, transforming complex data into scalable, high-impact analytical solutions.
Requirements
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