I am a data scientist working at Heidelberg Cement last 3 years on topics such as demand prediction, production planning and prediction of production parameters. Before I have worked at PwC as data analyst. I studied economics and econometrics and I have deep interest in ML explainability/transparency and merging various modeling approaches (Bayesian, classical ML, DL - Keras, Econometrical…) whatever works the best, no bias :D