Head, Process Data

About the role

Takeda is looking for a Head of Process Data to define and lead its global CMC Data Strategy within MSAT, enabling data-driven manufacturing and technology transfer across biologics, plasma, vaccines and synthetic molecules. As the global business process owner for CMC data, the role drives harmonized data standards, governance and digital capabilities. It is a highly visible leadership position at the intersection of manufacturing, data science and digital transformation, based in Zurich.

Key responsibilities

• 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 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 global team of process data experts and foster capability building across the wider CMC data community.
• Represent Takeda externally in scientific and industry forums to help shape CMC data standards and digital manufacturing practices.

Required profile

• Advanced degree (Master's or PhD) in a STEM discipline such as Chemical Engineering, Biochemical Engineering, Data Science, Life Sciences or a related field.
• At least 10 years of experience in the pharmaceutical or biotechnology industry, with significant exposure to CMC development or manufacturing environments.
• Proven track record leading cross-functional, geographically dispersed teams and influencing senior stakeholders.
• Strong leadership, communication and change management skills, with a commitment to developing people.

Required skills

• Data modelling, taxonomies, ontologies and governance frameworks applied to pharmaceutical process data.
• Understanding of manufacturing processes, data flows and integration across complex global organizations.
• Experience with FAIR data principles and platforms such as OSI PI, Databricks, AWS or equivalents.
• Knowledge of data integrity requirements and GxP-compliant data environments.
• Programming in Python and SQL.