Data Analyst for Payment & Collections area

In this role, you will contribute to building efficient, stable, and future-ready processes with a strong focus on customer experience, operational excellence, and digital innovation.

Odmeňovanie

About the position

• Development of business-oriented evaluation and control tools based on different data sources
• Analysis and evaluation of complex data sets using modern analytics methods on current data platforms.
• Data transformation: enrich, mix, enhance, filter, and consolidate data
• Preparation of reports and decision-making bases for a complex professional context
• Analysis, evaluation and further development of data structures and data-driven processes
• Development of viable data models to map business requirements
• Leverage advanced analytics and machine learning approaches to integrate analytics results into existing business processes and solutions
• Identification of trends, patterns and forecasts (e.g. predictive models)
• Preparation, presentation and derivation of recommendations for action for the department and management

What we expect

• Candidates with education suit the position
• University education (Bachelor's degree)
• English - Advanced (C1)
• German - Upper intermediate (B2)
• Solid functional understanding of payment and collections management and their end-to-end processes
• Knowledge of product and customer structures, or a strong willingness to quickly familiarize oneself with them
• Experience as a Data Analyst, Business Analyst, Analytics Consultant, or in a comparable role with a strong business orientation
• Experience in analyzing, modeling and preparing complex data sets, ideally in payment, collections, finance or revenue-related processes
• Strong understanding of end-to-end processes and the ability to structure and interpret data along these processes
• Hands-on experience in data modeling, data preparation and data transformation, e.g. enrichment, consolidation and filtering of data
• Experience in building reports, dashboards and decision-support materials for business units and management
• Confident handling of KPIs, performance metrics and steering indicators
• Experience with advanced analytics and/or machine learning approaches, e.g. forecasting, trend or pattern recognition, to generate business value
• Experience working with modern data platforms and integrating analytical results into existing processes and systems