Commercial Analytics Architect for pricing, forecasting, margin and CRM decision systems
I work where commercial data usually breaks down: between Sales, Finance, BI, IT and executive reporting. Based near Stuttgart, I fix pricing, forecasting, margin and CRM decision logic first, then design the systems that make those signals operationally trustworthy.
Technical depth stays visible, but it stays in service of decision quality, governance, and commercial control.
Selected Delivery Stack
The technology comes after the commercial problem is clear. This stack exists to make messy data more reliable, auditable, and usable in live decision workflows.
Forecasts, pricing, margin, CRM, and executive reporting each need different controls. The stack reflects that.
I favor tools that support traceability, validation, and safe rollout rather than black-box novelty.
Every choice is shaped by what leaders actually need to trust and act on each week.
Power BI carries the decision surface, Python handles repair and orchestration, and GPT-4 is applied only where narrative, retrieval, or controlled automation adds measurable value.
Controlled narrative, commentary, and document workflows
Executive reporting, semantic models, and margin walks
Automation, validation, APIs, and analytics engineering
Experiment tracking across 19+ training runs
Multi-task stock trading signal models
ML model serving and TelegramNotifications microservice
Semantic search for memoir pipeline and doc retrieval
Live automated stock trading execution
Machine Learning · ML Ops
End-to-end automated trading platform with TensorFlow multi-task signal generation, IBKR live execution, Databento L2 order book data, and W&B experiment tracking across 19 training campaigns.
Jan 2026 – Present
Medline, Stuttgart
2016 – 2022
Medline, UK & Australia
What's Next?
If forecasting, pricing, margin, CRM quality, or dashboard sprawl are slowing decision-making, start with a Commercial Analytics Health Check. From there, we can scope the right fix.