Senior Data Scientist & Technical Leader
Delivering production-ready ML solutions with $10M+ business impact across energy, healthcare, and manufacturing sectors.
Recent Achievements
Energy Grid Optimization
$2-5M annual value through intelligent demand response system achieving 5.4% grid reduction during extreme weather events.
PyTorch LSTM AWSHealthcare Risk Prediction
6.2M+ patients served with comprehensive ML framework bridging clinical risk prediction and resource optimization.
Healthcare ML GDPRPredictive Maintenance
$8.4M annual savings with 1-month payback through interpretable AI for aviation engine health monitoring.
Markov Chains ML EngineeringTechnical Leadership
Production ML Engineering with comprehensive testing, documentation, and quality review processes for AI-assisted development.
MLOps Team LeadershipTechnical Expertise
Machine Learning
- Deep Learning (PyTorch, LSTM, Transformers)
- Time Series Forecasting & Anomaly Detection
- Model Selection & Interpretable AI
- Production ML Engineering (MLOps)
Data Engineering
- Large-scale Data Processing (Pandas, Spark)
- Cloud Platforms (AWS, Azure, GCP)
- Real-time Data Pipelines
- Database Design & Optimization
Business Impact
- ROI Analysis & Business Case Development
- Stakeholder Communication & Management
- Regulatory Compliance (GDPR, HIPAA)
- Cross-functional Team Leadership
DACH Market Focus
Positioned for German, Austrian, and Swiss markets with expertise in:
- Energiewende – Grid modernization and renewable integration
- Industry 4.0 – Predictive maintenance and industrial IoT
- Healthcare AI – GDPR-compliant clinical decision support
- Regulatory Compliance – EASA, FDA, and EU standards
Key Differentiators
- Production-Ready Focus – Not just research, but deployable solutions
- Business Impact – Quantified ROI and cost savings
- Interpretable AI – Explainable models for safety-critical applications
- Quality Engineering – Comprehensive testing and documentation
Recent Highlights
Model Selection Philosophy – Chose interpretable Markov Chains over higher-performing Random Forest for aviation safety
Production ML Engineering – 95%+ test coverage with comprehensive quality review processes
Business Case Development – $8.4M annual savings with detailed ROI analysis and sensitivity testing