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.
