I help companies and individuals leverage the power of data and artificial intelligence for better decision-making and more efficient work.
Who I am and what I do for you
I am Michael Princ – a Data Scientist and ML Engineer from Prague. I combine 9 years of academic experience with practice from banking, the public sector, and freelance consulting. I understand not only the technology but also the business context – and I can explain complex concepts in a way that is easy to understand.
I help companies and individuals understand how data and AI can specifically improve their work. I don’t sell generic advice – I deliver functional solutions and share experience from dozens of real-world projects.
Data Science, ML models and consulting
I offer comprehensive data services – from data analysis through the development of ML models to their deployment in production.
🔬 Data Science consulting
Data analysis, predictive modeling, and visualization to understand your business. I will help you uncover patterns in data and transform them into concrete business decisions.
🤖 Machine Learning solutions and ML models
Development of ML models and end-to-end solutions for process automation and optimization. From design through training to deployment in production. I specialize in predictive models, scoring, MLOps, and Databricks pipelines.
🎓 Practical AI workshops
Practical workshops and training in the field of AI and data analytics. You will learn to use modern technologies for your work and projects. Workshops take place in small groups – the emphasis is on immediate usability, not dry theory.
Projects and case studies
⚙️ Unified ML Pipeline
Design of an end-to-end ML pipeline on the Databricks platform for a banking institution. The result: deployment of models shortened from 10 to 2 days, model accuracy +15%, pipeline −40% faster.
Technologies: Python, PySpark, Databricks, MLflow, Optuna, Docker
🏠 PENB Energy Label – estimate of energy performance
A web application that estimates the energy performance class of an apartment from operational data – without the need for a formal audit. It combines a thermodynamic RC model with meteorological data.
Available online: penb.michaelprinc.com
🤖 MCP Prompt Broker
An open-source routing system for AI agent instruction profiles based on the MCP (Model Context Protocol) protocol. A Frontier AI engineering project for 2025–2026.
GitHub: github.com/michaelprinc/MCP_prompt_broker
Portfolio of results – numbers that speak for themselves
| What I have achieved | Result |
|---|---|
| Improvement of lift statistics after updating production models | +30% |
| Shortening the deployment time of ML models | from 10 to 2 days (−80%) |
| Acceleration of ML pipeline – optimization of data sources | −40% |
| Improvement of campaign acquisition | +7% |
| Production ML models in the Unified Pipeline | ~100 |
| Years of experience in DS/ML | 7+ |
Practical AI workshops – for you and your company
In February 2026, a successful practical AI workshop was held at the Cafedu café in Vinohrady. I lead workshops in small groups (5–10 people) – I co-create the content with the participants according to their actual needs.
Workshop topics:
- Introduction to AI for beginners
- Practical use of AI tools (ChatGPT, GitHub Copilot, Cursor)
- Python for data analysis
- Customized corporate training
Free 30-minute introductory consultation
Blog – data science, MLOps and AI in practice
On the blog, I share experiences from real projects, technical procedures, and thoughts on data and AI.
Latest posts:
- PENB from operational data: where the estimate ends and the decision begins – March 23, 2026
- Unified Pipeline – Part 5: What I would do differently today – February 2026
- Unified Pipeline – Part 4: MLOps without the buzzwords – February 2026
- Practical workshop on artificial intelligence – February 2026
About me
I am a Data Scientist and ML Engineer from Prague. My journey has taken me through economics and academia – for 9 years I worked at Charles University, collaborated with the Office of the Government of the Czech Republic and the National Economic Council. In banking (Equa bank), I worked as an analyst in the product department – focusing on payment cards. I currently collaborate as a Data Scientist and ML Engineer with Raiffeisenbank a.s.
Besides client projects, I am dedicated to open source: PENB app, MCP Prompt Broker and WireGuard in Docker.
Open source and technology
On GitHub, I publish projects in the fields of Data Science, MCP engineering, Docker, and platform automation. You can find real examples of my work in my portfolio, and I continuously add technical experiments and utilities to public repositories.
Technologies
Python | PySpark | Databricks | Oracle DBMS | Hadoop | MLflow | Power BI | Docker | GCP | SQL (PL/SQL) | R | scikit-learn | CatBoost | MCP / LLM | PowerShell | Linux Bash