💡 Data Scientist with experience across Sports Analytics, Biomedical AI, and Autonomous Vehicle domain
📜 Patent Holder – Patented algorithm in Data Science (based on my Master’s thesis)
🎓 M.Sc. Informatics (Machine Learning & Analytics) – Technical University of Munich
⚙️ Passionate about building production-grade ML systems that are scalable, modular, and impactful

I build scalable Python applications, real-time data pipelines, and end-to-end projects in machine learning, data science, and Generative AI. Every solution follows industry-standard best practices, combining technical depth with real-world impact to deliver results that are both robust and commercially viable.

Tech Stack: Python, Poetry, Streamlit, MLflow, Optuna, Docker, CI/CD

• Real-time match analytics and player pass network visualizations
• End-to-end ML pipeline for pass outcome prediction, trained using match event data
• Integrated with MLflow for model tracking & reproducibility, and Optuna for hyperparameter optimization
• Modular architecture: separate data ingestion, processing, modeling, and visualization layers
• Built with production-readiness in mind — includes structured logging, environment isolation, and CI workflows

🎥 Watch Full Demo Video

Tech Stack: FastAPI, Apache Airflow, OpenSearch (BM25 + vectors), PostgreSQL, MinIO, Gradio, Docker Compose, Poetry (Ollama planned)

• Production-grade RAG with hybrid retrieval (BM25 + embeddings); infra-first Docker setup with service health checks
• Automated ingestion (arXiv → MinIO/Postgres) via Airflow; modular OOP design for swappable chunkers, embedders, and vector stores
• API + UI: FastAPI /ask with cited answers (WIP), Gradio frontend, CI scaffolding; evals via Recall@k/MRR; VPS-ready deployment

📋 Read the blog
💻 Access the webapp

Tech Stack: Apache Airflow, AWS S3, FastAPI, Pandas, Requests

• Production-grade ETL for weather data
• Orchestrated with Airflow DAGs, stored in S3 for scalability
• Designed to showcase data engineering best practices

💡 This profile is a growing showcase of my work in ML, Data Engineering, and GenAI. Each project follows industry-standard engineering practices, with a focus on scalability, modularity, and clarity.