Entwickler, Knowledge Engineer, Data Engineer, Data Scientist, Machine Learning Engineer
Im Kontext von stetiger wachsender Komplexität und Datenmengen: (teil)-automatisierte Datenintegration in Knowledge Graphs mit RDF und Linked-Data-Technologie und Durchführung von komplexen Analysen, Forcecasts und Was-Wäre-Wenn-Szenarien im Bereich der Business Analytics in Verbindung mit künstlicher Intelligenz im Agilen Umfeld.
Branchen
Knowledge Engineering & Künstliche Intelligenz
Technologien
Artificial Intelligence (AI), Python, SAS VIYA Analytics, Machine Learning, Deep Learning, Natural Language Processing, Visual Computing, Business Intelligence, Fuzzy Time & Logic, Geospatial Reasoning, Description Logic, First-order Logic, Applications, Forecasting, Simulation, Classification, Recommendation Systems, Knowledge Engineering (KE), Eccenca Corporate Memory, All things data, Integration, Quality, Access Control, Formats (XML/JSON/CSV/XLSX/Paquet), Graph and Relational Databases, Partioning, Dataspaces, Semantic Technologies, Knowledge Graphs, Linked Data, Ontology Engineering, RDF, RDFS, OWL, SPARQL, Reasoning & Logic, Data-driven Dashboarding, Data Project Management, Methodologies, Domain Analysis, Data Operations (DataOps), Virtualization (Docker), System Architecture, Clouds, Microsoft Azure, Amazon Web Services, Google Cloud, APIs, RESTful Web APIs, JDBC, SOAP, MS Graph / GitHub / GitLab / Jira / Confluence / Bamboo / Twitter / Spotify, Linux, Bash, Makefiles, Pipe, Cron Jobs, Access Control, Back-Ups