Description
The Senior Data Scientist will create connected data and knowledge capabilities that enable CMC Acceleration and modern digital manufacturing.
This role will transform fragmented scientific, manufacturing, laboratory, and quality information into governed, contextualized, and reusable data products that support faster decision-making, scalable analytics, artificial intelligence, and digital technology transfer.
The role combines hands-on technical expertise with leadership across complex, cross-functional initiatives, establishing reusable and technology-agnostic standards and partnering with data scientists, engineers, architects, CMC specialists, and delivery partners.
Responsibilities:
- Lead the design and delivery of data science and knowledge-engineering solutions for CMC Acceleration, translating scientific and manufacturing requirements into governed data products and semantic models.
- Define canonical data models, mapping rules, and contextualization patterns across FIL and UNS capabilities for equipment, process, recipe, material, batch, laboratory, and quality data.
- Develop and govern CMC ontologies, controlled vocabularies, taxonomies, and semantic relationships across products, processes, unit operations, equipment, analytical methods, materials, specifications, sites, and manufacturing capabilities.
- Convert document-based and scientific knowledge into structured, searchable, and traceable knowledge assets supporting knowledge graphs, retrieval, analytics, and AI-enabled workflows.
- Shape data-harness capabilities that ingest, contextualize, and expose information from manufacturing, laboratory, and enterprise sources, including MES, LIMS, ELN, historians, automation platforms, and external partners.
- Apply advanced analytics, machine learning, and graph-based methods to CMC and manufacturing use cases.
- Establish data quality, metadata, lineage, and observability requirements and partner with Quality, Security, Privacy, and Validation teams to establish controls for regulated use.
- Provide technical leadership across data scientists, data engineers, integration engineers, architects, CMC subject-matter experts, and strategic partners.
- Partner with Product Management, Manufacturing Technologies, MSAT, R&D, Quality, Regulatory, and site teams to prioritize use cases and define adoption plans.
- Represent the capability in architecture and data-governance forums and build internal expertise through coaching and communities of practice.
Requirements:
- Bachelor’s degree in Data Science, Computer Science, Bioinformatics, Engineering, Pharmaceutical Sciences, Applied Mathematics, or a related discipline.
- 6+ years of experience in data science, data modelling, knowledge engineering, industrial data, or advanced analytics.
- Experience leading complex cross-functional data, analytics, or technology initiatives.
- Experience delivering production-scale data or knowledge products within pharmaceutical, biotechnology, manufacturing, laboratory, or another regulated environment.
- Experience designing canonical data models, mappings, ontologies, taxonomies, knowledge graphs, or semantic layers across multiple data sources.
- Experience integrating or contextualizing manufacturing or laboratory data from systems such as MES, LIMS, ELN, historians, automation systems, or enterprise platforms.
- Experience establishing data quality, metadata, lineage, testing, or operational controls for data solutions.
Benefits:
- Health care and other insurance benefits (for employee and family)
- Retirement benefits
- Paid holidays
- Vacation
- Paid caregiver/parental and medical leave