Summary
Zain Sohail is a research engineer in machine learning with 11 years of experience applying data-driven solutions to large-scale scientific and audio signal problems across academia and industry. He builds robust data pipelines and reproducible ML systems—most recently at HEAD acoustics—after engineering TB-scale distributed processing tools (Dask, Xarray) for physics datastreams at DESY. Comfortable bridging research and production, he has implemented real-time signal-processing for hearing-aid prototypes and automated CI, testing and metadata provenance to keep complex workflows auditable. Trained in engineering physics (Oldenburg, DTU) and currently deepening data-science expertise at RWTH Aachen, he brings a physics-first approach to ML that prioritizes data integrity and observability over model-centric fixes. An understated strength is his focus on practical tooling—packages, notebooks and visualization—that make large, multi-dimensional datasets directly usable by scientists and engineers.
11 years of coding experience
6 years of employment as a software developer
Bachelor of Engineering - BE, Engineering Physics, 3.8, Note: 1.3, Bachelor of Engineering - BE, Engineering Physics, 3.8, Note: 1.3 at Carl von Ossietzky Universität Oldenburg
Master of Science - MS, Data Science, Master of Science - MS, Data Science at RWTH Aachen University
Technical University of Denmark
General Certificate of Education Advanced Level (A Level), Mathematics, Chemistry, Physics, English, General Certificate of Education Advanced Level (A Level), Mathematics, Chemistry, Physics, English at Al Waha International School
English, Urdu, geman