Design of multi account setup for scalable ML operations environment including access management, policy management, Security Design and definition of governance processes

• CICD setup for cloud platform and container based software rollout
• Interface development and integration of on premise data sources.
• Design and implementation of Kappa architecture
• Set up data lake with data catalog and data governance as a centralized source for Data science teams
• MLOps for existing ML solutions and migration to cloud platform
• Continuous monitored re-training process
• Scale out of existing ML models to multiple production lines
• ML and data quality monitoring system
• Migration of internal data processing logic to cloud native scalable serverless architecture
• Coordination and implementation of security requirements and network design with company IT

• Automated reporting of business data
• Adjusting and optimizing data collection process
• Development of software components to streamline processes and harmonize data collection

• Predictive maintenance & machine learning
• Statistical forecasting methods
• Data mining methods
• Detailed production configuration based on data driven decision making
• Automated product quality classification
• Development of business analytics tool
• BI reporting & Dashboarding
• Data collection and web-based survey development
• Automated AI based waste classification
• AI based keywording of technical documents
• Project Management and Project Lead

• Operationalization of predictive maintenance ML models for online monitoring of asset qualities
• Model monitoring for critical AI systems
• Migration of traditional on premise systems to cloud solutions
• Cloud native implementation of audit documentation for process digitalization and optimization

• Data quality assessment / data screening
• Time series analysis
• Outlier detection / data error detection
• Statistics for industrial development reports

• Development of data based support for decision processes
• DWH development & incorporation of various data sources
• Machine learning & data preprocessing for automated route planning for cargo trains
• Project Management in Scrum System

• Installation, setup and administration of a database management system
• Quality management of the data warehouse
• Processing and integration of data sources
• Monitoring and statistical analysis of traffic and mobility data
• Development of forecasting models
• Seminar in statistics and R training for ÖBB employees
• Running ML models and web-based prediction application in Azure

• Statistical consulting in predicting drug response for pre-clinical research
• Robust IC50 estimation for dose response curves
• Consulting for sample sizes & multiphase designs
• Biostatistics training of Arsanis research team

• Development of a parser for Google RSS feeds
• Information retrieval from website information and RSS content
• Monitoring and data / text mining with R
• Multivariate data analysis, predicting break-in probabilities

• Statistical analysis and modelling of traffic and pavement condition data
• Monitoring and data mining of large amounts of data
• Application of statistical big data methods: machine learning, random forest, regression

• Development of the study design and review of the study protocols of clinical trials (phase II study in the field of oncology)