Bio
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Daniel Byrne is a seasoned data scientist with expertise in predictive modeling and visualization. At Sovendus, he developed and tested models utilizing PyTorch, pandas, numpy, and SQL to forecast client spend on campaigns, and created interactive visualizations to communicate results to sales teams and customers. Byrne holds a Bachelor of Science in Engineering from the University of Connecticut, where he also excelled in the Cybersecurity Club and Mathematics Club, with a focus on Theory & Algorithms and Lambda Calculus.
Experience
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Sovendus
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Karlsruhe, Baden-Württemberg, Germany
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Data Science Intern
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Mar 2022 - Sep 2022
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Karlsruhe, Baden-Württemberg, Germany
Developed & tested models to predict affect of client spend on campaigns with the company using tools such as pytorch, pandas, numpy, python, SQL & matplotlib. Also developed visualizations in communication with the sales team to communicate those results to customers.
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Education
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2017 - 2022University of Connecticut
Bachelosr of Science in Engineering, Computer Science and Engineering -
2021 - 2022Karlsruhe Institute of Technology (KIT)
Austauschprogram, Informatics -
2017 - 2022University of Connecticut
Bachelors, Matematics -
2017 - 2022University of Connecticut
Bachelor of Arts - BA, German Studies
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Industry Focus. “Computer Software”
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