Hey! I am a Research Engineer (Data Scientist) in DS&AI > Data Assets and Insights Solutions (DAIS) > Scientific Digital Solutions. I am responsible for implementing scientific solutions (namely: Aelixir, cellenium, ChemogenomicsDB, Bambus ...) and integrating data to make it easily accessibly and analyzable across the Bayer R&D Org. Feel free to reach out : dan.plischke@bayer.com My Professional Experience: Data Scientist: R&D Scientific Digital Solutions September 2020 - Present Corporate Student: Business Information Systems Oktober 2017 - Oktober 2020 My Academic Background: Master of Science - MS, Information Systems 路 (2020 - now) Humboldt University of Berlin Bachelor of Science - B.Sc., Business Information Systems 路 (2017 - 2020) The Berlin School of Economics and Law
Hubble is a pioneering data hub that continuously integrates and enriches terabytes of external scientific textual data to support insight generation along the R&D value chain. It opens opportunities for statistical analyses, large-scale text-mining and other data science methodologies to tease out important details and detect trends within e.g., patents, scientific literature, and grants. The Hubble platform is available Bayer-wide, and offers API access for data scientists. This allows large scale, programmatic analysis as well as integration into processes and platforms. Hubble is a cornerstone of our digital transformation journey within R&D. It serves many users, systems and processes with key data & analyses by answering ~2 million queries per week. We continue to extend the platform to best support insight generation and scientific decision making with a precision medicine focus. For more information contact: Astrid Rheinl盲nder.
Team R&D Master Data Management (MDM) is responsible for the processes and technologies used to ensure the consistency, accuracy, and completeness of critical data that is used across various departments and functions within the R&D organization. MDM plays a crucial role in ensuring the reliability of scientific and clinical data used for research, drug development, regulatory submissions, and decision-making. Key responsibilities include: define and implement data standards & policies, develop and maintain a centralized master data repository, establish data quality controls, ensure data steward- and ownership, manage data integration from different sources and systems, ensure compliance with regulatory requirements and provide training and support for end-users across R&D to ensure proper use and interpretation of data.
