Dist. Scientist, Research Science

Job description

Job Description Distinguished Scientist – CMC Lighthouse Pillar 2: Digitally Enabled Technology Transfer | Brick 1 Lead Position SummaryThe Distinguished Scientist will provide scientific, technical, and strategic leadership for Brick 1 within CMC Lighthouse Pillar 2, Digitally Enabled Technology Transfer. This individual will define and lead an integrated strategy and execution plan for establishing, maturing, connecting, and deploying the requisite models across CMC domains and modalities. The role will lead product, process, analytical, manufacturing, and technology-transfer modeling capabilities to drive improved process and analytical understanding and render transfer decisions faster, more predictive, and more consistent across development, manufacturing and commercialization. Strategic MandateDefine the model landscape: Identify the requisite mechanistic, statistical, hybrid, empirical, and AI/ML models needed across CMC domains to enable digitally supported technology transfer. Integrate across domains: Establish a coherent strategy connecting product, process, analytical, formulation, materials, equipment, scale-up, control strategy, and manufacturing models. Plan across modalities: Develop a coordinated, risk-based roadmap that addresses common needs and modality-specific requirements across the CMC portfolio. Drive deployment and reuse: Convert modeling strategy into prioritized use cases, fit-for-purpose model suites, business process changes and implementation, and measurable improvements in transfer execution. Key ResponsibilitiesScientific and Technical LeadershipServe as the scientific authority for the integrated portfolio of models required to enable digitally supported CMC technology transfer. Establish a cross-modality framework for determining which models are required, where common approaches can be reused, and where modality-specific solutions are necessary. Guide the development and application of mechanistic, statistical, hybrid, empirical, and AI/ML models, with clear definition of intended use, assumptions, uncertainty, applicability, verification, and validation. Set expectations for model lifecycle management, including prioritization, development, qualification, deployment, maintenance, reuse, and retirement. Anticipate emerging scientific, regulatory, and technology trends and translate them into a pragmatic CMC modeling roadmap. Portfolio and Delivery LeadershipOwn and continuously refine the Brick 1 integrated modeling strategy, cross-modality roadmap, milestones, dependencies, resource needs, and value case. Create a transparent inventory and gap assessment of existing and required models across CMC domains and modalities. Prioritize modeling investments based on technology-transfer risk, portfolio leverage, scientific value, maturity, and readiness for deployment. Lead cross-functional teams from model concept and development through qualification, implementation, adoption, sustainment, and reuse. Establish clear decision rights, governance, technical review mechanisms, and escalation paths for the CMC modeling portfolio. Manage interdependencies with other Lighthouse bricks and enterprise initiatives to connect model outputs to technology-transfer workflows and decisions. Communicate progress, risks, decisions, and value realization to scientific and executive governance bodies. Model Governance, Quality, and ComplianceEstablish fit-for-purpose governance for the CMC model portfolio, proportionate to model risk, intended use, and decision impact. Partner with Quality, Regulatory, Manufacturing, IT, and scientific functions to define expectations for model documentation, traceability, verification, validation, change control, access, and lifecycle oversight. Define model-readiness criteria for technology transfer, including required inputs, boundary conditions, uncertainty, applicability domain, performance expectations, and ownership. Ensure models and model-enabled workflows are appropriately governed for their intended use, including GxP applicability where required. Influence and Capability BuildingBuild alignment among process, analytical, formulation, product, manufacturing, quality, regulatory, supply, and digital modeling stakeholders across organizational boundaries. Influence senior leaders and technical communities to adopt a shared CMC modeling strategy and coordinated investment plan. Develop playbooks, model-development standards, reuse patterns, and communities of practice that accelerate adoption and reduce reinvention. Mentor scientists, engineers, modelers, and technical leaders; strengthen organizational capability in model-informed development and technology transfer. Represent the organization in selected external consortia, collaborations, and scientific forums related to advanced CMC modeling. Measures of SuccessClear coverage of priority modeling needs across CMC domains and modalities, with agreed ownership and delivery plans. Increased use of qualified models in technology-transfer decisions, risk assessments, scale-up, control strategy, and site implementation. Improved integration and reuse of models, methods, assumptions, and learnings across programs, modalities, and manufacturing sites. Earlier identification and mitigation of transfer risks through predictive and model-informed insights. Reduced time and manual effort required to support transfer decisions and reconcile technical assumptions. Demonstrated adoption by development teams, receiving sites, and external partners. Clear value realization tied to cycle time, right-first-time execution, deviations, technical risk, and speed to supply. QualificationsRequiredPh.D. in chemical engineering, chemistry, biochemistry, pharmaceutical sciences, systems engineering, applied mathematics, data science, or a related field, with >15 years of relevant industry experience; or an equivalent combination of education and experience. Recognized scientific or technical leadership in CMC development, technology transfer, manufacturing sciences, process development, analytical development, or model-informed development. Demonstrated success defining and leading complex, cross-functional technology strategies or portfolios from concept through sustained implementation. Strong understanding of CMC development-to-manufacturing handoffs, scale-up, control strategy, process and analytical models, and regulated product development. Broad knowledge of mechanistic, statistical, hybrid, empirical, and AI/ML modeling approaches and their fit-for-purpose application across CMC domains. Ability to develop integrated strategies that balance common capabilities with the distinct scientific and operational needs of different modalities. Ability to communicate complex technical concepts clearly to scientists, engineers, modelers, quality and regulatory partners, and senior executives. Track record of influencing across organizational boundaries and resolving ambiguity, competing priorities, and complex dependencies. Leadership CapabilitiesEnterprise thinking: Connects domain-specific modeling needs to a coherent, scalable strategy across CMC and modalities. Scientific credibility: Uses deep technical judgment to select fit-for-purpose modeling approaches and distinguish durable capabilities from isolated solutions. Outcome orientation: Focuses teams on measurable scientific and business value rather than model development alone. Inclusive influence: Builds shared ownership across disciplines, functions, sites, and geographies. Pragmatic innovation: Balances ambition with scientific rigor, risk-based delivery, compliance, usability, and operational realities. Talent multiplication: Develops others, creates technical communities, and raises modeling fluency across CMC. Key RelationshipsThe role will partner closely with CMC development functions, process and analytical development, formulation and product sciences, manufacturing sciences and technology, cli