I am a "Senior Insight Solutions Lead" which means that I work in DAIS team and try to generate novel insights for our R&D (and beyond) organization

I am a pharmacist from Rio de Janeiro-Brazil and I work as a computational chemist at Bayer since 2021 in the Computational Molecular Design department in Wuppertal. I work side by side with chemists on different projects using our digital tools to design small molecules that maybe one day will help patients! I am passionate about my work and I have the opportunity to also be part of the Steering Group for Transformation and Leadership in the Drug Discovery Science to help transforming the way we work and communicate.

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 · (2020 - now) Humboldt University of Berlin Bachelor of Science - B.Sc., Business Information Systems · (2017 - 2020) The Berlin School of Economics and Law

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.