Associate Engineering Fellow -Process Knowledge & Data Architecture

Role: Associate Engineering Fellow in Process Knowledge & Data Architecture within Synthetic Molecule Process Development (SMPD), focusing on designing and implementing scalable digital data systems to support pharmaceutical process development. Responsibilities include establishing a unified process knowledge layer, designing connected data architectures linking chemistry, process parameters, and analytical results, and enabling model-informed development and AI workflows through structured, reusable data assets. The role involves defining data standards, governance, and FAIR principles, integrating disparate data sources, and collaborating with cross-functional teams across process science, modeling, automation, and IT to promote data-driven decision-making and digital transformation. The position also entails supporting digital twin architecture, overseeing digital platform deployment, and fostering a data-centric culture. Qualifications: PhD in Chemical Engineering, Chemistry, Data Science, or related field with 7+ years, or MS with 13+ years, or BS with 15+ years of relevant experience. Expertise in data architecture, modeling, and integration within pharma R&D or manufacturing, including familiarity with ELN, LIMS, MES, cloud data platforms (AWS, Azure), and regulatory data integrity (cGMP, ALCOA+). Skills in data governance, FAIR data principles, and cross-functional stakeholder influence are essential. Preferred skills include ontologies, knowledge graphs, digital twin development, and advanced process control. The role requires approximately 10% travel and is based in Cambridge, MA.