Roles & Responsibilities: Lead conversations with business collaborators to elucidate semantic models of pharmaceutical business concepts, aligned definitions, and relationships. Negotiate and debate across collaborators to drive alignment and create system-independent information models, taking a data-centric approach aligned with business data domains. Develop comprehensive business information models and ontologies that capture industry-specific concepts, including CMC, Clinical, and Operations data. Facilitate whiteboarding sessions with business subject matter experts to elicit knowledge, drive interoperability across pharmaceutical domains, and interface between data producers and consumers. Educate peers on the practical use and differentiating value of Linked Data and FAIR+ data principles. Champion standards for master data & reference data. Formalize data models in RDF as OWL and SHACL ontologies that interoperate with each other and with relevant industry standards like FHIR and IDMP for healthcare data exchange. Build a broad semantic knowledge graph that threads data together across end-to-end business processes and enables the transformation to data-centricity and new ways of working Apply pragmatic semantic abstraction to simplify diverse pharmaceutical and healthcare data patterns effectively. Basic Qualifications: Doctorate degree OR Masters degree and 4 to 6 years of Data Science experience OR Bachelors degree and 6 to 8 years of Data Science experience OR Diploma and 10 to 12 years of Data Science experience Preferred Qualifications: About the role You will play a key role in a regulatory submission content automation initiative which will modernize and digitize the regulatory submission process, positioning Amgen as a leader in regulatory innovation. The initiative uses state-of-the-art technologies, including Generative AI, Structured Content Management, and integrated data to automate the creation, review, and approval of regulatory content. Role Description: The Sr Data Scientist is responsible for developing interconnected business information models and ontologies that capture real-world meaning of data by studying the business, our data, and the industry. With a focus on pharmaceutical industry-specific data, including Clinical, Operations, and Chemistry, Manufacturing, and Controls (CMC), this role involves creating robust semantic models based on data-centric principles to realize a connected data ecosystem that empowers consumers. The Information Modeler drives seamless cross-functional data interoperability, enables efficient decision-making, and supports digital transformation in pharmaceutical operations. Functional Skills: Must-Have Skills: Proven ability to lead and develop successful teams. Strong problem-solving, analytical, and critical thinking skills to address complex data challenges. Deep understanding of pharmaceutical industry data, including CMC, Process Development, Manufacturing, Engineering Quality, Supply Chain, and Operations. Advanced skills in semantic modeling, RDF, OWL, SHACL, and ontology development in TopBraid and/or Protg. Demonstrated experience creating knowledge graphs with semantic RDF technologies (e.g. Stardog, AllegroGraph, GraphDB, Neptune) and testing models with real data. Highly proficient with RDF, SPARQL, Linked Data concepts, and interacting with triple stores. Highly proficient at facilitating, capturing, and organizing collaborative discussions through tools such as Miro, Lucidspark, Lucidchart, and Confluence. Expertise in FAIR data principles and their application in healthcare and pharmaceutical data models. Good-to-Have Skills: Experience in regulatory data modeling and compliance requirements in the pharmaceutical domain. Familiarity with pharmaceutical lifecycle data (PLM), including product development and regulatory submissions. Knowledge of supply chain and operations data modeling in the pharmaceutical industry. Proficiency in integrating data from various sources, such as LIMS, EDC systems, and MES. Hands-on data analysis and wrangling experience including SQL-based data transformation and solving integration challenges arising from differences in data structure, meaning, or terminology Expertise in FHIR data standards and their application in healthcare and pharmaceutical data models. Soft Skills: Exceptional interpersonal, business analysis, facilitation, and communication skills. Ability to interpret complex regulatory and operational requirements into data models. Analytical thinking for problem-solving in a highly regulated environment. Adaptability to manage and prioritize multiple projects in a dynamic setting. Strong appreciation for customer- and user-centric product design thinking.