Agentic systems and 15 years of analytics turned into applied ML.
Data Scientist and AI Engineer with 15 years in analytics across finance, telecom, insurance, and gaming. I build applied AI systems, currently prototyping revenue forecasting at InnoGames with time-series foundation models, PyMC, and TabPFN while completing my M.Sc. at Leuphana University. My thesis develops an agent that turns planning text into inputs for probabilistic revenue forecasting.
Foundation models and agent-compiled text covariates for game revenue.
My M.Sc. thesis asks whether an agent that compiles the studio’s planning text into forecasting covariates improves probabilistic three-month revenue forecasts at InnoGames beyond the calendar flags already in use.
Work in progress; submission December 2026. Further details once the thesis is submitted.
Fifteen years in analytics, from telecom M&A research to probabilistic forecasting.
My work is closest to problems where forecasting, analytics engineering, and decision support meet. I care about models that can be inspected, monitored, and explained: Bayesian inference, structured memory, and production forecasting workflows rather than one-off notebooks.
I am finishing an M.Sc. in Management & Data Science at Leuphana University as a Deutschlandstipendium scholar while prototyping revenue forecasting at InnoGames. From April 2027, I am open to full-time Data Scientist and AI Engineer roles in Germany.
Selected Projects: Agentic AI, knowledge graphs, Bayesian inference
What I work on
I build forecasting and decision-support systems for teams that need defensible predictions, not just performant models. My current focus is applied LLM and agentic systems for analyst workflows, hierarchical Bayesian inference, and time-series foundation models running on cloud and self-hosted infrastructure. The projects below span all three: knowledge-graph question answering, hierarchical Bayesian customer lifetime value, and a multi-agent founder assistant.
ChefTreff AI Hackathon: Founder Assistant
Multi-agent assistant that helps founders launch a company in Germany, covering business plan, marketing plan, and legal documentation.
Knowledge Graph Question Answering
Team project: SPARQL-based question answering over structured knowledge graphs, enabling natural language queries over RDF knowledge bases.
KVG ML Route Modelling
Team project with a regional transit partner: applied ML to model and predict transportation routes, combining geospatial data with predictive modelling.
Neo4j Graph Analysis of Artist Influence Networks
Graph database solution using Neo4j and Cypher to analyse artists' influence and cluster musical lineages.
Hierarchical Bayesian Pareto/NBD: Replication of Abe (2009)
Implemented and validated the hierarchical Bayesian Pareto/NBD model from Abe (2009) on the canonical CDNOW dataset.
ChefTreff AI Hackathon: Product Detection
Built in 24 hours: a computer vision pipeline for identifying broken or damaged objects from product imagery.
Writing on agentic systems and probabilistic ML
Looking for a data scientist or AI engineer in Germany, Hamburg, Munich or Berlin, from April 2027?
I bring the most value in forecasting automation, scalable analytics pipelines, and agentic system design, with a focus on open-source and cloud-native architectures.
My work fits six kinds of teams well:
- Insurance and reinsurance analytics. Underwriting segmentation at Absolute Insurance plus current Bayesian forecasting research, applicable to Munich's insurance cluster and beyond.
- Gaming and consumer products. Currently prototyping revenue forecasting and building analytics infrastructure at InnoGames in Hamburg, including Microsoft Fabric migration and Power BI dashboards.
- AI-native startups and applied AI labs working on LLM systems, agentic architectures, and retrieval. My thesis builds an agent that turns planning text into inputs for probabilistic revenue forecasting.
- Telecom and network analytics. Eight years at MTS covering market analysis and M&A across Indian, Serbian, Slovenian, and Moldovan markets, relevant to Munich's operator headquarters.
- Global tech firms and platform teams in Hamburg, Munich, and Berlin where forecasting, applied ML, and production analytics scale across products.
- Startups and scale-ups shipping production ML and agentic systems as core product, not pilots.
I'm comfortable in English C1 and German B2-C1. Fifteen years in analytics have been about shipping for international teams across finance, telecom, insurance, and gaming.