Data Scientist

• Designing, implementing, evaluating, and improving statistical models and machine learning algorithms (classic and deep neural networks)
• Evaluating promising technologies (e.g. frameworks, libraries, third-party integrations)
• Staying up to date with the state of ML applications in education (esp. adaptive learning and predictive learning analytics)
• Creating technical documentation, incl. patent applications
• Sharing work results internally and externally (e.g. talks and workshops at conferences and meetups, journal publications)

We work in agile teams in which members can wear many hats, so besides building models, or data scientists also have the opportunity to work on other project aspects, e.g. designing efficient solutions for large-scale data processing, operationalizing and optimising models, etc.