Senior Data Scientist

GSK • King of Prussia, PA

8d • $145,200 - $242,000

About The Position

The Senior Data Scientist will create connected data and knowledge capabilities to support CMC Acceleration and modern digital manufacturing. The role transforms fragmented scientific, manufacturing, laboratory, and quality information into governed, contextualized, reusable data products that enable faster decision-making, scalable analytics, artificial intelligence, and digital technology transfer.

Working across data science, semantic modelling, manufacturing integration, and knowledge management, the role helps shape data patterns across Factory Integration Layer (FIL), Unified Namespace (UNS), mapping and contextualization services, enterprise ontologies, CMC knowledge assets, and data-harness capabilities. It combines hands-on technical expertise with leadership across complex cross-functional initiatives, establishing reusable, technology-agnostic standards and partnering with data scientists, engineers, architects, CMC specialists, and delivery partners.

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.

Nice To Haves

• Master’s degree or PhD in Data Science, Computer Science, Bioinformatics, Engineering, Pharmaceutical Sciences, Applied Mathematics, scientific computing, or a related discipline.
• Experience using Python and SQL to deliver data science, analytics, graph, semantic, or machine-learning solutions.
• Experience with Factory Integration Layer (FIL), Unified Namespace (UNS), or similar industrial data integration and contextualization patterns.
• Experience with semantic technologies and standards such as RDF, OWL, SHACL, SPARQL, or comparable graph and ontology technologies.
• Experience developing or applying knowledge graphs, enterprise ontologies, controlled vocabularies, taxonomies, or metadata platforms.
• Experience with streaming, time-series, event-driven, batch, graph, cloud, or scalable data-processing technologies.
• Experience applying advanced analytics or machine learning within CMC, pharmaceutical development, manufacturing, or laboratory environments.
• Knowledge of responsible AI, explainability, privacy, security, data integrity, and risk-based validation within regulated environments.
• Experience working with GxP-regulated data and technology environments.
• Experience working across scientific, manufacturing, data, engineering, Quality, and technology teams.
• Experience providing technical leadership, coaching specialists, or establishing standards and reusable technical patterns.
• Ability to translate complex scientific, manufacturing, and technical concepts for different stakeholder groups.
• Strong technical writing and communication skills.

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 for 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.

Benefits

• Annual bonus
• Eligibility to participate in a share-based long-term incentive program, dependent on role level
• Health care and other insurance benefits for employees and family
• Retirement benefits
• Paid holidays
• Vacation
• Paid caregiver, parental, and medical leave

What This Job Offers

• Job Type: Full-time
• Career Level: Senior