• Anforderungsaufnahme, Beratung, Softwareentwicklung sowie technische Umsetzung in Kundenprojekten rund um Daten, Big Data, Data Analytics, Data Science sowie Business Intelligence. • Modellierung und Optimierung von Datenarchitekturen und BI-Systemlandschaft der Kunden. • Durchführung interner und externer Coachings, Trainings und Mentoring für Young Professionals bei entsprechender Berufserfahrung. • Kundenworkshops, Reviews und Analysen sowie Pre-Sales-Aktivitäten zur Kundengewinnung und -bindung.

• Lead our payment and fraud analytics strategy, driving data-driven decisions that optimize financial performance and protect our gaming ecosystem • Define and execute the vision for payment analytics, moving beyond standard reporting to predictive insights that improve success rates and conversions • Analyze payment data using SQL and create compelling dashboards with Tableau, PowerBI, or Looker to inform strategic decisions • Implement strategies to reduce payment declines, recover failed transactions, and identify conversion bottlenecks • Lead chargeback mitigation efforts by analyzing trends and implementing automated triggers to protect merchant accounts • Develop detection logic to identify bonus abuse, multi-accounting patterns, and synthetic identities • Collaborate with cross-functional teams to build risk-scoring models that balance security with player experience

• Extract, query, and manipulate data using SQL from relational databases and cloud data warehouses. • Analyze large transactional and consumer datasets to identify trends, patterns, and business insights. • Build and maintain structured datasets that support recurring reports and business analyses. • Calculate key business metrics such as household penetration, market share, purchasing behavior, and category trends. • Work with raw and semi-structured data, cleaning and categorizing information as needed. • Validate data outputs and perform quality checks to ensure data accuracy and integrity. • Collaborate with internal teams to support reporting needs and answer business questions through data. • Translate complex datasets into clear findings and recommendations.

• Lead and execute analytics projects focused on patient-journey and line-of-therapy mapping, Brand analytics. • Analyze structured claims and patient datasets such as DRG, IQVIA, McKesson, Symphony claims. • Conduct exploratory data analysis (EDA) to assess treatment patterns, pathways and utilization. • Support HEOR/HCRU analyses including prevalence, burden, incidence and cost-of-illness studies. • Develop and present client-facing insights using dashboards, PowerPoint and visual analytics. • Build and optimise SQL queries, pipelines; use Excel and Python for automation and analysis. • Collaborate with HEOR, market-access, strategy and engineering teams.