Teaching Course "Wellbeing with Data Analytics" / "Wohlbefinden Verbessern mit Data Analytics": - Teaching "Introduction in R" and "Data Analytics Basics" Exercises - Development of custom Tooling / Visualizations with React.JS - Preliminary Data Analysis using RResearch:- Support in Literature Research, Experimental Designs and extensive Statistical Analysises (R)- Development of Experimental Environments such as Web-Shop and Apps (React.JS)Other activities:- Creation and Research for Course Slides

Development of a Managed Service in the area of IAM / Access Creep Detection using Process Mining Algorithms (AI/ML) 1. Logdata (Active Directory and others) audit to structure pre-processing and evaluate data mining possibilities 2. Script-based development of an Attribute Change-Log Deriver 3. Analysing the generated "WAL" during different relevant lifecycle events of a company: - founding and unwinding of companies, - on- and off-boarding, promotions and switching of departments of employees and - on-boarding of new applications 4. Evaluation and implementation of relevant algorithms for pattern and anomaly detection in Golang and Python (Scikit-learn, PM4py) 5. Dashboard-based (PowerBI) visualisations of the detected issues (access creep) and anomalies in the role-structure. Presentation at KPMG Data Driven Services, cross-validation with real data from an KPMG Alliance Partner.6. Move to ElasticSearch and Kibana for custom visuals: Development of Kibana-Plugins using React.JS7. Pitch at various KPMG Customers and Partners8. Extension of the PoC with additional algorithms, focusing on employees switching departments and employee off-boarding9. Development of standalone React.JS + MobX WebApp using well-known Kibana components from the Elastic UI Library