Senior Director, Advanced Pharmacometrics, Quantitative Pharmacology and Pharmacometrics - Immu

Overview

We are seeking an accomplished scientific leader to join the Quantitative Pharmacology and Pharmacometrics - Immuno‑Oncology (QP2‑IO) team as Senior Director
, Advanced Pharmacometrics. The 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 the 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.

• 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.

• 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.
• 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.

• 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…