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 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.

Qualifications

Required

• Ph.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 Capabilities

• Enterprise 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 Relationships

The role will partner closely with CMC development functions, process and analytical development, formulation and product sciences, manufacturing sciences and technology, clinical and commercial manufacturing sites, Quality, Regulatory CMC, Supply Chain, Information Technology, modeling and simulation communities, data and digital organizations, and external manufacturing and technology partners.

Required Skills:

Analytical Thinking, Bioanalytical Techniques, Biochemistry, Chemistry, CMC Strategy, Data Analysis, Experimentation, Influencing Skills, Manufacturing, Product Development, R&D Strategy, Regulatory CMC, Scientific Leadership, Strategic Foresight, Technology Transfer

Preferred Skills:

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As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics.  As a federal contractor, we comply with all affirmative action requirements for protected veterans and individuals with disabilities.  For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit:

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The primary location for this posting is:

USA - New Jersey - Rahway

Where required by law, the compensation range for this role is provided below.

The salary range for the primary location of this role is:

$210,400.00 - $331,100.00

This range reflects the Company's reasonable expectation of the base salary applicable to this role at the time of posting. An employee’s position within the salary range will be based on several factors including, but not limited to relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs. The successful candidate will be eligible for annual bonus and long-term incentive, if applicable.

We offer a comprehensive package of benefits. Available benefits include medical, dental, vision healthcare and other insurance benefits (for employee and family), retirement benefits, including 401(k), paid holidays, vacation, and compassionate and sick days. More information about benefits is available at https://jobs.merck.com/us/en/compensation-and-benefits.

Additional location(s): Please note the salary range above applies to the Primary Location of the position. Where a role has other listed locations, different compensation guidelines may apply. You may find the salary ranges for additional locations below. If the salary range is not listed for the location you are applying to, our Talent Acquisition team will provide further information to you relevant to your location.

Additional location(s) Compensation Information:

San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance

Los Angeles Residents Only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance

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Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company.  No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails. 

Employee Status:

Regular

Relocation:

VISA Sponsorship:

Travel Requirements:

Flexible Work Arrangements:

Hybrid

Shift:

Valid Driving License:

Hazardous Material(s):

Job Posting End Date:

11/11/2026

*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.