Freelancer profile translated to English.
Back to original languageAbout Marco
I develop data-driven solutions with a focus on Analytics, Data Engineering, and AI Automation. My goal: to automate processes with LLMs, RAG systems, and agent-based workflows and integrate them into existing data architectures.
My current focus is on developing AI automation solutions: RAG systems for semantic search across document repositories, multi-agent workflows with LangGraph and CrewAI, and process automation with n8n and LLM integration. I develop individual solutions with API integration that can be integrated into existing systems.
The foundation for this is many years of practice in Data Engineering and Backend Development: building analytical data pipelines with Python (Pandas, SQL, GeoPandas), developing backend applications with Django, creating interactive dashboards (Power BI, Superset, Streamlit), and integrating heterogeneous data sources in a management consultancy.
Before that, I was a Research Engineer at TU Darmstadt for three years, where I developed control and monitoring systems for a particle accelerator and performed complex measurement data analysis with Python.
Education: M.Sc. Physics, certified Data Scientist
German
Native or bilingual
English
Conversational
Can work on-site
Darmstadt (up to 50km)
Experience
- Datengetriebenes Unternehmen (vertraulich)Data ScientistBANKING AND INSURANCEOctober 2023 - Today (2 years and 8 months)
- Backend development and participation in building a data ecosystem for an internal B2B SaaS product in the insurance sector with a Django backend
- Optimization of the database architecture for more efficient data processing and improved system performance
- Integration of external data sources via REST APIs to expand the data basis for analyses and models
- Development and optimization of ETL pipelines to ensure consistent and high-quality data
- Agile feature development within the Scrum/Kanban framework with code reviews, retrospectives, and continuous integration
- Refactoring of existing codebase to increase maintainability
- StackFuelData Scientist (Training Program)EDUCATION AND E-LEARNINGApril 2023 - June 2023 (2 months)
- Comprehensive training in supervised and unsupervised learning with Scikit-Learn (regression, classification, clustering, dimensionality reduction)
- Building scalable data pipelines, applying regularization techniques, outlier detection, and model interpretation
- Developing neural networks with Keras and working with big data technologies such as PySpark and SparkSQL
- In-depth study of data visualisation, model evaluation, and practical implementation of complex ML projects with Python
- Independent execution and presentation of portfolio projects, from selection and agile implementation to result preparation for stakeholders
- Data Science Graduate (StackFuel)Independent Further TrainingJuly 2023 - September 2023 (2 months)
- Following an intensive training program, targeted deepening of knowledge in deep learning methods, especially neural networks and their application in practical projects
- Focus on working with Keras and TensorFlow, as well as engaging with current developments in the field of artificial intelligence
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Education
- Certificate "Data Scientist", Data ScienceStackFuel2023Certificate "Data Scientist", Data Science
- Master of ScienceTechnische Universität Darmstadt2020Master of Science - MS, Physik