Head, Process Data

As Head of Process Data, you will define and lead Takeda's global CMC Data Strategy within MSAT, enabling the next generation of data-driven manufacturing and technology transfer across biologics, plasma, vaccines, and synthetic molecules. You will serve as the global business process owner for CMC data, driving harmonized data standards, governance, and digital capabilities that support operational excellence and accelerate scientific innovation. This is a highly visible leadership role at the intersection of manufacturing, data science, and digital transformation.

How you contribute

• Define and govern global CMC data standards, including taxonomies, ontologies, metadata frameworks, and data models across all modalities.
• Establish and lead the global CMC Data Model to ensure consistency across manufacturing sites, functions, and technologies.
• Build and oversee global CMC data governance frameworks, including stewardship, ownership, and data quality standards.
• Enable data-driven manufacturing and technology transfer by ensuring access to structured, FAIR, and analysis-ready process data.
• Partner closely with Digital, Data & Technology (DD&T) and local MSAT teams to implement business rules and scalable digital solutions.
• Drive CMC data quality, integrity, and GxP compliance across the global manufacturing network.
• Lead, coach, and develop a high-performing global team of process data experts while fostering capability building across the wider CMC data community.
• Represent Takeda externally in scientific and industry forums, helping shape the future of CMC data standards and digital manufacturing practices.

• Advanced degree (Master's or PhD) in a STEM discipline such as Chemical Engineering, Biochemical Engineering, Data Science, Life Sciences, or a related field.
• Minimum of 10 years of experience within the pharmaceutical or biotechnology industry, with significant exposure to CMC development or manufacturing environments.
• Demonstrated expertise in data modelling, taxonomies, ontologies, and governance frameworks applied to pharmaceutical process data.
• Strong understanding of manufacturing processes, process data flows, and integration of data across complex global organizations.
• Experience working with FAIR data principles and modern data platforms such as OSI PI, Databricks, AWS, or equivalent technologies.
• Proven track record leading cross-functional and geographically dispersed teams while influencing senior stakeholders and technical experts.
• Strong knowledge of data integrity requirements and GxP-compliant data environments.
• Programming experience in Python and SQL, combined with high learning agility, curiosity, and a passion for innovation and digital transformation.
• Excellent leadership, communication, and change management skills, with a strong commitment to developing people and driving engagement across global teams.