Thomas Schleider

Background

About Thomas Schleider

As a Data Scientist, I can write and work on projects for software that processes data to extract insights from it. I can apply and have a profound understanding of Machine Learning including Deep Learning techniques to automate data-driven processes. Part of my typical workflow is to handle or compose datasets including Knowledge Graphs based on Semantic Web technologies (RDF, SPARQL a.o.) including Ontologies (OWL) and visualize insights that my code gains. My preferred coding language to deal with data is Python, which includes a.o. the libraries Pandas, Scikit-learn, Matplotlib and NumPy as well as the frameworks PyTorch and Tensorflow for deep neural networks. This includes good handling of typical software engineering tools like Git and Docker. Furthermore, I am mostly but not exclusively specialized in Natural Language Processing (a.o. SpaCy, HuggingFace, NLTK), from LLMs to Transformer-based models like BERT, GPT-2/3 and word embeddings. Personally, I am open, very curious and believe that the best results can be gained through collaboration.