Helyne A is a data-driven research engineer and board member based in Berlin with nine years of experience at the intersection of neuroimaging, machine learning, and environmental sensing. She led the development of sensor-integrated downscaling models and the backend weather-station database at VineForecast, combining field-facing engineering with cloud-native deployment on GCP. Trained in diffusion MRI research (PhD work at Leipzig/Max Planck) and skilled in Python, SQL, Docker, Django and TensorFlow, she translates complex scientific questions into production-ready data systems. Now focused on climate and urban sustainability, she blends rigorous experimental methods from cognitive neuroscience with pragmatic software engineering to optimize resource management. An unusual strength is her ability to bridge domain research and product engineering—turning advanced imaging and modeling techniques into operational tools for real-world environmental problems.
9 years of coding experience
4 years of employment as a software developer
Data Science, Data Science at Le Wagon
PhD Candidate, PhD Candidate at Leipzig University
Master of Science (MSc), Master of Science (MSc) at King's College London
Bachelor of Arts (BA), Bachelor of Arts (BA) at Emerson College
Contributions:20 commits, 5 PRs, 12 pushes in 27 days
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