Juliane Mai is a software developer and applied-math-trained data scientist with eight years of experience building large-scale hydrologic and data platforms that translate complex environmental models into decision-ready tools. Fluent in German and based in Kitchener, she pairs research-grade expertise in model calibration, data assimilation and HPC with practical software skills in Python, C/C++, Fortran and SQL to deliver production-ready pipelines and portals like CaSPAr and Hydrohub. Her background spans academia and industry—leading research clusters and consulting for organizations such as BC Hydro and Natural Resources Canada—so she navigates stakeholder-driven projects from prototype to deployment. Notably, her work blends operations research and environmental modeling, enabling robust uncertainty quantification in forecasting systems that inform real-world water-management decisions.
8 years of coding experience
7 years of employment as a software developer
Master of Science - MS Applied Mathematics, Master of Science - MS Applied Mathematics at HTWK Leipzig
This GitHub is providing all data and scripts used to produce all figures in publication "Application of Parameter Screening To Derive Optimal Initial State Adjustments for Streamflow Forecasting".
Contributions:3 releases, 1 PR, 15 pushes in 1 year 7 months
Contributions:1 release, 128 commits, 5 pushes in 2 years 2 months
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