Data Scientist

At Euronet, we don’t just build payment solutions—we shape the future of how the world moves money as a global leader in payments processing and cross-border transactions. From mobile wallets and card issuing to real-time payment platforms, our products drive digital transformation in 160+ countries.

We’re looking for a Data Scientist to become a part of our talented team.

Your Life @Euronet

As a #Euronetter, you’ll be part of a truly human-centered culture built on trust, respect, and cooperation. Your contributions will be recognized, and your growth supported through meaningful career development opportunities.

• Data preparation and analysis: Collect, clean, combine, and explore data using Python and SQL, identifying patterns, anomalies, and data-quality issues.
• Forecasting: Support the development, testing, and improvement of models used for operational and cash-planning forecasts.
• Time series analysis: Explore trends, seasonality, calendar effects, and other factors influencing business.
• Model evaluation: Compare predictions with actual results, calculate performance metrics, and help investigate forecast errors.
• Operational support: Help monitor existing forecasting processes, investigate issues, and document findings with support from experienced colleagues.
• Automation and AI: Contribute to small improvements using Python, Microsoft tools, and approved AI solutions.
• Visualization and communication: Prepare clear charts, reports, and presentations that explain findings to technical and business colleagues.
• Collaboration and documentation: Work with Cash Management and other stakeholders to understand business needs and maintain clear, reproducible analyses.

• Some practical experience working with data, gained through projects, studies, internships, or an entry-level role.
• Basic to intermediate Python skills, including familiarity with pandas and NumPy for data preparation and analysis.
• Basic knowledge of machine learning, such as regression, training and test datasets, overfitting, and model evaluation. Initial experience with scikit-learn is sufficient.
• Basic understanding of statistics and forecasting concepts, including averages, variability, correlation, trends, and seasonality.
• Basic SQL skills, including filtering, joins, grouping, and aggregations.
• Ability to create and explain simple data visualizations, using tools such as Matplotlib, Seaborn, Plotly or similar libraries.
• Familiarity with Microsoft Excel and everyday Microsoft 365 tools, such as Teams and SharePoint.
• Awareness of AI tools and their limitations, including the importance of checking outputs and protecting confidential information.
• An analytical approach, attention to detail, and willingness to ask questions and learn.
• Ability to explain your work clearly and collaborate with others.
• Polish and English skills sufficient for everyday communication and working with technical documentation.
• Availability to work from our Warsaw office under the hybrid work model.
• A degree, ongoing studies, or equivalent practical learning in Data Science, Statistics, Mathematics, Econometrics, Economics, Computer Science, or a related field would provide a useful foundation

What Will Help You Thrive

• These are additional advantages, not requirements:
• A project involving time series forecasting, predictive modeling, or a real business dataset.
• Basic familiarity with Git and version control.
• Initial experience working in a Linux environment.
• Familiarity with Power BI or Power Query.
• Basic knowledge of Microsoft Power Automate, or experience creating a simple automated workflow.
• Initial experience with generative AI, prompt writing, or using approved AI assistants to support coding, analysis, or documentation.
• Awareness of time-based validation, data leakage, or reproducible analytical workflows
• You should demonstrate a basic understanding of generative AI tools and their practical application in a business environment. This includes using AI responsibly to improve efficiency, support decision-making, generate content, analyze information, and automate routine tasks while maintaining appropriate data privacy and quality standards.

At Euronet, we are an Equal Opportunity Employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, or national origin, age, disability status, genetic information, protected veteran status, or any other characteristic protected by law.

• Competitive and fair salary package including various benefits
• Professional and international working environment
• Opportunity to work on challenging projects
• Further career opportunities