I build production-ready ML systems that bridge the gap between research and real-world impact. From optimizing neural networks with C++ backends to developing LLM-powered data integration pipelines, I turn complex algorithms into scalable solutions that solve actual business problems.
An implementation of a convolutional neuronal net with pytorch to classify weather conditions from pictures
A full-stack application for training and visualizing a linear regression model and a neuronal network using C++, Node.js, and React.
A python implementation of the Simplex algorithm to solve linear optimization problems. With a streamlit interface and additional features for visualization (also sensitivity analysis) and a LLM integration.
Hi, I'm Nicolas Schneider — a Data Scientist and Developer with a strong foundation in mathematics, machine learning, and large language models. I enjoy turning complex problems into practical, scalable tools that deliver real-world impact.
With over two years of hands-on experience, I've applied Python and LLMs to solve challenges across diverse domains. I'm driven by curiosity and focused on building solutions that are both technically sound and operationally valuable.
B.Sc. in Applied Mathematics at University of Applied Sciences Bielefeld
Grade: 2.3
Interviewer
SOKO Institut
M.Sc. in Optimization and Simulation at University of Applied Sciences and Arts Bielefeld
Working Student / Data Scientist
Diamant Software
Working Student / Data Analyst
4brands Reply
Master Student & Scientist
Fraunhofer Institute for Production Technology IPT
A skeptical, solution-oriented look at what RSI is, what it is not, and how to tell the differenc...
24 Sep 2025Welcome to my blog!
26 Apr 2025Email: schneidernicolas90@gmail.com