Noel Schwabenland

I am a Python-focused Data & AI consultant with experience in designing and implementing practical, data-driven solutions for complex technical and business challenges.

I currently work as a Data Science Consultant at KPMG AG, where I support clients in building reliable Python-based systems for analysis, automation, and decision support. My work typically involves structuring problems from first principles, developing maintainable solutions, and validating technical approaches through functional prototypes before scaling.

Alongside my consulting work, I am a Master’s student in Physics, which provides a rigorous analytical foundation and a disciplined approach to modeling, abstraction, and quantitative reasoning. This background is particularly valuable in projects that involve non-trivial data processing, algorithmic logic, or mathematically grounded system design.

In addition, I have contributed to automated AI workflows in scientific research, including pipeline development in the context of drug discovery at Saarland University, and I have experience working across the stack on technical systems that combine backend logic with user-facing components.

I typically engage in projects where ideas need to be clarified, tested, and turned into working technical solutions within a short timeframe. My focus is on clear communication, fast iteration, and delivering results that can be evaluated and extended with confidence.