Dist. Scientist, Research Science

Merck; New Jersey; On-site; USD 180,000 - 300,000; Full time

Job summary

Merck in New Jersey seeks a Distinguished Scientist to provide scientific, technical, and strategic leadership for Brick 1 within CMC Lighthouse Pillar 2, Digitally Enabled Technology Transfer. You will define and lead an integrated strategy to mature, connect, and deploy models across CMC domains and modalities.

The role drives modeling capabilities across product, process, analytical, and manufacturing interfaces, enabling faster, more predictive transfer decisions from development through

Qualifications

• Lead integrated CMC modeling strategy across modalities.
• Experience with mechanistic, statistical, hybrid, empirical, and AI/ML models.
• Strong governance and lifecycle management for models.

Responsibilities

• Define and lead the integrated modeling strategy for Brick 1.
• Coordinate cross-modality roadmaps and model inventories.
• Ensure model governance and lifecycle management across the portfolio.

Skills

Scientific leadership

Strategic planning

Cross-functional collaboration

AI/ML modeling

Model governance

Job description

Job Description

Distinguished Scientist -

CMC Lighthouse Pillar 2: Digitally Enabled Technology Transfer | Brick 1 Lead

Position Summary

The 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 Mandate

• Define 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 Responsibilities

Scientific and Technical Leadership

• Serve 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 Leadership

• Own 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 Compliance

• Establish 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 Building

• Build 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 Success

• Clear coverage of priority modeling needs across CMC domains and modalities, with agreed ownership and delivery plans.
• Increased