Michael Schaarschmidt
Senior Data Scientist
Bonn, North Rhine-Westphalia, Germany
Summary
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Rockstar🎓
Top SchoolMichael Schaarschmidt is a Senior Data Scientist based in Bonn with nine years of experience turning business problems into data-driven solutions at Deutsche Telekom. He blends enterprise analytics and reporting expertise from a long telecom career with hands-on machine learning research—contributing to open-source reinforcement learning (Tensorforce) by implementing Normalized Advantage Functions and robust learning setups. A PhD student and lifelong learner with advanced studies in organization and database development, he challenges the status quo and champions new-work approaches within large organizations. Comfortable moving between production reporting, experimental RL models, and strategic steering, he uniquely pairs pragmatic business impact with deep technical curiosity.
9 years of coding experience
5 years of employment as a software developer
Diploma of Advanced Studies, Diploma of Advanced Studies at Institut für Organisation & Management an der Steinbeis-Hochschule Berlingeprüfter Datenbankentwickler (ils), geprüfter Datenbankentwickler (ils) at ILS - Institut für Lernsysteme GmbH
Github Skills (6)
neural-network10
machine-learning10
deep-learning10
tensorflow10
python10
reinforcement-learning10
Programming languages (2)
Github contributions (5)
tensorforce/tensorforce
Nov 2016 - Apr 2018
Tensorforce: a TensorFlow library for applied reinforcement learning
Role in this project:
Machine Learning Engineer
Machine Learning EngineerContributions:663 commits, 93 PRs, 342 pushes in 1 year 5 months
Contributions summary:Michael contributed to the development of a Normalized Advantage Functions (NAF) implementation for reinforcement learning, suggesting a focus on model-based reinforcement learning techniques. They also made improvements to the model and its configurations. The contributions included implementation of a general learning setup, as well as testing and debugging of the core functionality, indicating a strong understanding of reinforcement learning concepts.
tensorflow-librarytensorforcereinforcement-learningdeep-reinforcement-learningmachine-learning
michaelschaarschmidt/BOAT
Feb 2017 - May 2017
Contributions:32 pushes in 3 months
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