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Ανδρέας Δαρσακλής

@0005744

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I build practical machine learning pipelines for forecasting, anomaly detection, and data analysis.

Greece

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What I'm looking for

I'm looking for an opportunity to apply Python, data science, and machine learning skills to practical data-driven problems while growing through hands-on work in a collaborative technical environment.

I've built end-to-end machine learning projects across electricity forecasting, anomaly detection, clustering, and market-basket analysis using Python.

For WattAhead, I combined electricity load, weather, and calendar data into a time-series pipeline, achieving 3.43% MAPE and reducing MAE by 42% versus a previous-day baseline on an unseen 2020 holdout.

My BSc thesis examined how data-quality degradation affects business process discovery and anomaly detection, evaluating KNN, DBSCAN, Isolation Forest, LOF, and multiple process-discovery algorithms on real and synthetic event logs.

During my software development internship at Web2Learn, I contributed to Python-based data processing, data extraction, transformation, and semantic-data workflows in a research-oriented environment.

Experience

Work history, roles, and key accomplishments

Software Development Intern

Web2Learn

Mar 2026 - May 2026 (2 months)

Worked with Python-based data processing and structured datasets in a research-oriented software environment, contributing to data extraction, transformation and semantic-data workflows.

Python Data Processing Data Extraction data transformation

Education

Degrees, certifications, and relevant coursework

Aristotle University of Thessaloniki

Bachelor of Science, Computer Science

Grade: 8.18/10

Graduated in 2026 with an average score of 8.18/10. Coursework included Machine Learning, Neural Networks, Data Mining, Databases, Statistics/Probability, and Artificial Intelligence.