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Senior Director, Advanced Pharmacometrics, Quantitative Pharmacology and Pharmacometrics – Immuno-Oncology (Hybrid or Remote)

Merck

Remote · Rahway, NJ, US$210k – $331k

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About this role

Job Description

We are seeking an accomplished scientific leader to join the Quantitative Pharmacology and Pharmacometrics – Immuno-Oncology (QP2‑IO) team as  Senior Director , Advanced Pharmacometrics. QP2‑IO is part of the Global Clinical Development organization and is responsible for clinical pharmacology and pharmacometrics strategy and execution for oncology assets, from candidate nomination through registration.

Our Senior Directors are recognized experts in quantitative drug development and possess a deep, integrated understanding of both the science and the strategic, end‑to‑end dimensions of oncology drug development. Reporting directly to Executive Director and Section Head, QP2‑IO, the Senior Director will lead advanced pharmacometrics strategy and implementation to inform key oncology portfolio decisions.  

The ideal candidate is an accomplished scientific leader with deep expertise in oncology drug development and has a proven track record in shaping and delivering impactful oncology MIDD strategies. This individual must have extensive experience in population PK/PD, tumor dynamics and survival modeling, Bayesian inference, and model-based meta-analysis (MBMA), along with strong cross-functional influencing skills in a matrixed environment. The role includes substantial internal and external engagement, including with vendors and regulatory agencies.

Primary Responsibilities

Strategic Leadership

• Lead quantitative pharmacology strategy across the oncology portfolio, ensuring alignment with program goals and organizational priorities. • Develop and implement long-range plans for integrating MIDD, pharmacometrics, data science, and Bayesian modeling approaches to accelerate and de-risk oncology drug development. • Partner with senior leaders in Clinical Development, Translational Medicine, Biostatistics, Regulatory, and Data Science to define modeling strategies that influence program design and key decisions.

Scientific & Technical Leadership • Oversee development of advanced pharmacometrics modeling including but not limited to population PK/PD, tumor dynamics and survival modeling, advanced models to inform dose selection, clinical design, and benefit–risk assessments. • Champion the use of Bayesian methods including hierarchical and joint modeling, and prior-data integration to strengthen oncology decision-making. • Ensure high-quality, regulatory grade pharmacometric deliverables for submissions, label negotiations, and scientific advice meetings. • Stay at the forefront of emerging methodologies including AI/ML and promote innovation in modeling tools, computational frameworks, and analytics platforms.

Team Leadership & Development

• Lead, mentor, and develop a team of quantitative scientists in a matrixed role. • Foster a culture of scientific rigor, excellence, collaboration, and innovation.

Cross-Functional Collaboration

• Collaborate with QP2 leads to design efficient, model-informed clinical trials • Work closely with Translational, Clinical, Biostatistics functions to integrate advanced modeling into decision frameworks.

Regulatory & External Engagement

• Contribute to regulatory strategy through preparation of pharmacometric reports, briefing documents, and presentations. • Represent the company at scientific conferences, external collaborations, consortia, and industry working groups.

Minimum Education • Ph.D.  in pharmacokinetics/pharmacodynamics, pharmacometrics, mathematics, statistics/biostatistics, chemical/biomedical engineering, or a related discipline with  at least 10 years  of pharmaceutical drug development experience, including substantial experience in pharmacometrics roles.

OR • Master’s, PharmD, or equivalent degree  with  at least 15 years  of pharmaceutical drug development experience, with a demonstrated record of increasing responsibility, independence, and leadership in similar roles.

Required Experience and Skills • Extensive and in‑depth experience in application of MIDD in oncology drug development to drive impactful development decisions. • Deep proficiency in advanced pharmacometrics methods such as: • Bayesian hierarchical models, joint models of tumor and survival, drop-out models, MBMA, advanced clinical trial simulation methods, integrating PROs and RWD into traditional NLME approaches.   • Hands-on experience with software such as NONMEM, Pumas, Stan, R, and/or other Bayesian platforms.

• Advanced analytical skills, including designing and interpreting clinical trials, problem solving, critical data analysis, interpretation, and decision making. • Understanding of oncology biology, translational pathways, and clinical endpoints (e.g., ORR, PFS, OS, tumor dynamic modeling). • Demonstrated impact across multiple therapeutic modalities, including, for example, antibody–drug conjugates (ADCs), T cell engagers (TCEs) monoclonal antibodies (mAbs), cytokines, and small molecules. • Experience integrating AI/ML methods into clinical pharmacology and pharmacometrics workflows to advance model‑informed drug development, optimize study design, and support regulatory decision‑making is preferred. • Excellent written and verbal communication skills, with a track record of effective cross‑functional collaboration, stakeholder management in a matrixed environment and ability to influence at senior levels.

#QP2 #Eligible for ERP

The remote position is only applicable for those that are not within commutable distance to primary sites noted in posting.  If commutable, the position will be hybrid. Please note that standard commute is (less than)

Required Skills: Biopharmaceutical Industry, Clinical Development, Cross-Functional Collaboration, Data Modeling, Data Science, Data Visualization, Drug Development, Effective Written Communication, Model Driven Development, Modeling Software, Nonlinear Mixed Effects Modeling (NONMEM), Oncology Drug Development, Pharmacodynamics, Pharmacokinetics, Pharmacometrics, Verbal Communications Pre

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