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Moderna

Sr. Director, Head, Quantitative Systems Pharmacology

Moderna

Director

$196,700 – $353,400

Listed on Moderna’s own careers site. You apply with them directly — we never stand between you and the employer.

What this role is

Lead the quantitative systems pharmacology function at a major mRNA therapeutics company, defining how mechanistic modeling and model-informed drug development drive early-stage decisions across oncology and immunotherapy programs. This role suits a seasoned quantitative scientist with deep expertise in translational pharmacology and the ability to influence strategy across discovery, preclinical, and clinical teams.

Our summary, not Moderna’s wording. The full posting is on their site.

Skills this role names

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What they ask for

Required

  • Ph.D. in systems pharmacology, bioengineering, applied mathematics, pharmacology, or related quantitative discipline (or MS with 20+ years experience)
  • 10+ years industry experience in QSP or mechanistic modeling
  • At least 7 years supporting oncology drug development
  • Deep immuno-oncology expertise
  • Proven track record applying mechanistic and translational models from preclinical through clinical stages
  • Deep understanding of PK/PD, systems biology, disease pathway modeling, and biomarker integration
  • Demonstrated scientific leadership and mentoring of quantitative scientists
  • Proficiency in modeling platforms such as MATLAB/SimBiology, Monolix, R, or Python
  • Strong communication skills translating quantitative findings for multidisciplinary audiences
  • Ability to operate strategically while remaining hands-on in modeling
  • Experience contributing to regulatory filings and Health Authority interactions with model-informed approaches

Nice to have

  • Experience with T cell engagers, adoptive cell therapy, or cancer immunotherapy approaches
  • Experience in mRNA or novel therapeutic modalities like gene therapy or biologics
  • Familiarity with PBPK modeling, virtual populations, or digital-twin simulation
  • Experience building infrastructure or toolchains for scalable modeling and data integration
  • Track record of scientific publications and external visibility

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