My name is Florian Wilhelm, a Data Scientist with a PhD in Mathematics, based in Cologne, Germany.
I combine a background in applied mathematics and high-performance computing with more than a decade of experience in data science, recommender systems, and large-scale data platforms.
I enjoy building robust AI systems, leading expert teams, and contributing to the open-source community.
Academic Background
I studied mathematics at the Karlsruhe Institute of Technology (KIT) with a focus on numerical mathematics and computer science.
My PhD research centered on Parallel Preconditioners for an Ocean Model in Climate Simulations, where I developed numerical methods to model fluid dynamics efficiently on high-performance clusters.
As Head of the Research Lab for Application and Innovation at KIT, I coordinated industry-funded projects and supervised bachelor and master students.
Professional Experience
I started my career as a Data Scientist at Blue Yonder, the leading provider of AI solutions for retail, where I worked on predictive analytics projects such as demand forecasting, replenishment optimization, and price trend analysis for global clients.
Later, I joined inovex, a German IT project house, where I am now Head of Data Science. In this role, I lead a heterogeneous team of data scientists and ML engineers and drive innovative AI projects across industries. Examples include:
- Building large-scale recommender systems (e.g. for mobile.de)
- Developing fraud and account takeover detection for e-commerce
- Applying learning-to-rank methods to improve search quality
- Research projects in OCR with deep learning, NLP interfaces for SQL, and reinforcement learning
My daily work combines strategic leadership with hands-on engineering. I bring models into production using technologies such as Python (NumPy, SciPy, scikit-learn, Pandas, Polars), Spark, and Snowflake/Snowpark. I also have solid experience with cloud platforms (Google Cloud, AWS) and a strong background in high-performance computing from my academic years.
Open Source & Community
Open source is an important part of my professional life.
On Github you’ll find projects like PyScaffold, a Python project template generator, and Ultimate Notion, a modern Python client for the Notion API.
I also contribute to the Python Data Science stack (NumPy, SciPy, Scikit-Learn, Polars, Pandas, Matplotlib, JupyterLab), helping to push the ecosystem forward.
Talks & Publications
I regularly share my work with the community:
- A selection of my talks is available on YouTube.
- My scientific publications can be found on Google Scholar publications.
Get in Touch
I enjoy connecting with people who are passionate about data, AI, and applied mathematics.
If you’d like to collaborate, discuss data science, or invite me to speak, feel free to reach out via LinkedIn.