Janis Klaise is a Data Scientist at Seldon primarily working on algorithms to provide rich information beyond raw predictions for live ML systems (e.g. model explanations, outlier detection, model confidence, concept drift). Ongoing projects include the development of the open-source ML explainability library Alibi and work on productionising ML models via seldon-core (open source platform) and seldon-deploy (enterprise option). Previous speaking experience include various data science meet-ups (PyData London, Google Developer's Group, Data Science Initiative, Tensorflow London).