Digital Chemistry, Manufacturing, and Controls (dCMC) is a cross-divisional digital transformation initiative that will enable the pipeline by establishing a digital continuum of data from development through manufacturing for Merck's products and processes.
Requirements
- Understanding of data within the CMC (Chemistry, Manufacturing, and Controls) domain, including experience in analytical testing, manufacturing processes, and laboratory development.
- Basic understanding of regulatory authoring processes and the role of data in regulatory filings, including how data supports submissions and the importance of accuracy and traceability.
- Familiarity with source systems such as LIMS, Veeva, and document formats like PDF, enabling effective data extraction, validation, and integration.
- Experience in data standardization, modeling, and semantic ontologies to define standards, maintain data models, and enhance data interoperability.
- Strong analytical skills with attention to detail and accuracy in data handling.
- Understanding of master data management and manufacturing ontologies to support consistent data definitions, relationships, and governance.
- Data engineering and experience with extract, transform, load tools and scripting techniques.
Responsibilities
- Data Standardization and Source Integration: Define and implement data standardization rules and practices across multiple source systems.
- Data Model Development and Maintenance: Contribute to the creation and refinement of the data models that represent regulatory filing sections and their underlying data relationships.
- Data Product Support and Evolution: Develop and maintain data products that enable auto-generation of regulatory filing content.
- Cross-Functional Collaboration and Communication: Work closely with regulatory authoring, IT, data strategy, and source system teams to align on data requirements and understanding integration priorities.
- Support the extraction, transformation, and validation of process and analytical data to ensure consistency and quality before auto generation into regulatory documentation.
- Assist in documenting data models, metadata, and data lineage to support transparency and traceability.
- Support iterative updates to data models as new sources are connected or regulatory requirements evolve.
Other
- Bachelor's of Science in a related discipline (e.g., Chemistry, Chemical Engineering, Pharmaceutical Sciences, Data Analytics, Information Systems), with a minimum 4 years of experience
- Master's degree in a related discipline (e.g., Chemistry, Chemical Engineering, Pharmaceutical Sciences, Data Analytics, Information Systems), with a minimum of 3 years of experience
- Ph.D in a related discipline (e.g., Chemistry, Chemical Engineering, Pharmaceutical Sciences, Data Analytics, Information Systems), with relevant academic Experience
- Travel Requirements: No Travel Required
- Employee Status: Regular
