Data-Driven Adaptation Engineer

• Configure and adapt G+D-developed algorithms for BPS systems to meet customer currency specifications
• Analyze banknote data (sensor data, images, measured features) to create customer-specific adaptation profiles
• Validate algorithm performance through testing, simulation, and statistical evaluation
• Identify optimization opportunities along every step of the adaptation process
• Use Python for exploratory data analysis, automation tasks, and algorithm evaluation
• Develops/implements systems to perform basic evaluation of adaptation artifacts according to state-of-the-art quality standards
• Apply statistical methods to improve adaptation quality
• Build and optimize data pipelines and notebooks in Databricks to analyze large volumes of banknote data
• Identify patterns, anomalies, and insights to support continuous improvement
• Collaborate with algorithm development, product management, customer service, and field engineers
• Communicates with colleagues inside the Adaptation group to leverage optimization and automation opportunities
• Prepare documentation, reports, and presentations for internal and customer-facing workshops
• Support complex customer adaptation projects worldwide
• Identify own personal and professional development needs

• Degree in Computer Science, Electrical Engineering, Mathematics, Data Science, Physics, or related field
• Solid foundation in statistics, data analysis, and analytical problem-solving
• Hands-on experience with Python (pandas, numpy, matplotlib, Jupyter)
• Experience working with Databricks, PySpark, or similar data platforms
• In-depth understanding of state-of-the-art software development practices (linting, code style, version control systems)
• Ability to understand and work with algorithms and signal/data processing workflows
• Very good English skills
• German is a plus

German is a plus