Senior System Manager

Process Manager for Data Sciences Services & Solutions

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.

Scientific work in Pharma R&D requires a reliable high-quality body of data and knowledge. Bayer Pharma R&D has an extremely large amount of scientific data. The use of a Data Catalog significantly improves the findability of data and serves as a key pillar in the implementation of a comprehensive data strategy.

The Proprietary Information Management team, PIM, takes care of processes and systems related to either Compliance or Data Governance. Please talk to us if you need help with some cross-functional or collaboration-related topic or if you are interested to learn more about compound-related processes, compliance checks, lab notebook systems and similar things. For more information contact: Friederike Stoll.

The SCLM4Future project together with the PRINCE (Preclinical Information Center) project as well as the CONDAS (Connecting Data for Science) team is an excellent example for a successful cross-functional collaboration between CD&O, RED preMed and DS&AI within Research & Development but also between Platform IT and external partners. Together the team achieved to overcome legacy manual processes, redundant maintenance work, and functional silos by introducing new digital solutions and concepts with a strong collaborative mindset. The newly released SCLM 2.0 (Standard Codelist Maintenance) & PTO (Preclinical Terminology and Ontology) systems will enable our organization to improve the quality of controlled terminologies with regards to standard codelists and codes while reducing maintenance time and effort. This will have a positive impact on the code/codelist consistency across clinical and preclinical, as well as the compliance to regulatory requirements (e.g. CDISC (Clinical Data Interchange Standard Consortium) Controlled Terminology). The approach to share our knowledge as well as our efforts across functions will be an important step to archive our goals to increase data quality, interoperability and reusability – or to make a long story short: to make our data even more FAIR. For more information contact: Daniela Bergann.