Paschalis Lagias is a Senior Data Scientist based in London with nine years of experience blending data science, GIS and software engineering to deliver production-ready ML solutions. He has a strong mathematical foundation and extensive Python expertise (six years), applying libraries like scikit-learn, XGBoost and TensorFlow to time-series forecasting, explainability (LIME/SHAP) and large-scale spatial/point-cloud segmentation. At fintech startup Zinia he improved AutoML workflows and LSTM forecasting pipelines, while freelance work for engineering consultancies produced 90%+ segmentation accuracy and halved 3D scan processing times. His background in surveying and GIS (MScs in Data Science and GIS) gives him a practical edge when turning messy geospatial data into automated ETL and database-backed products. Methodical, collaborative and documentation-focused, he thrives on making complex models transparent and deployable across cross-functional teams.
9 years of coding experience
7 years of employment as a software developer
Master of Engineering - MEng Land and Engineering Surveying, Master of Engineering - MEng Land and Engineering Surveying at Aristotle University of Thessaloniki (AUTH)
Master of Science (MSc) Data Science, Master of Science (MSc) Data Science at Birkbeck, University of London
Contributions:35 commits, 33 pushes, 1 branch in 1 year
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