Principal Scientist - Mathematical Modeling Lead

ABOUT AMGEN

Amgen harnesses the best of biology and technology to fight the worlds toughest diseases, and make peoples lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond whats known today.

ABOUT THE ROLE

The department of clinical pharmacology, modeling and simulation seeks a motivated, and mathematical modeler/ quantitative scientist / applied mathematician or statistician who will drive the development and execution of computational modeling and simulation strategies to enable nextgeneration pharmacometric analyses.

We are seeking a subject matter expert with experience in quantitative approaches to inform drug development. Proficiency in one or more of the following areas is highly desirable: applied mathematics, multivariate statistical methods, AI/ML-based modeling and analytics, data warehousing, automation of complex data workflows, data engineering and emerging computing technologies. Knowledge of pharmacokinetic/pharmacodynamic (PK/PD) modeling will be useful.

In this role, the Principal Scientist will contribute across a broad range of activities, including, curation and visualization of complex datasets, developing and industrializing novel computational methods for QSP and PK/PD modeling and automation of pharmacometric workflows. The candidate is also expected to establish, lead and mentor a team of junior scientists to deliver on department objectives.

This role is ideal for a scientific leader with quantitative science/applied mathematics background and interest in PK/PD and exposureresponse modeling, who is passionate about integrating quantitative methods, data science, and emerging technologies to influence critical development and regulatory decisions at a global level.

Key responsibilities may include:

• Independently developing and implementing analytics workflows to manage and analyse large, complex datasets from diverse sources, including realworld data.
• Driving innovation through the application of modern data architecture, data science engineering, data modeling, and advanced computing methodologies.
• Planning and executing PK/PD analyses that integrate pharmacokinetics, pharmacodynamics, patient characteristics, and disease biology to optimize dose selection, dosing regimens, and study designs.
• Mentoring and managing junior scientific staff to support modeling and simulation activities and collaborating closely with other modelers to implement data and modeling workflows for innovative pharmacometric projects.
• Collaborating with crossfunctional partners, including observational research, health economics and outcomes research, statistics, and clinical biostatistics teams, to enable platformlevel analytics and modeling workflows.
• Providing scientific thought leadership, guidance, and strategic input, and contributing to the external scientific community through publications and conference presentations.

Preferred Qualifications:

• Doctorate degree and 8 years of clinical pharmacology experience OR Masters degree and 12 years of clinical pharmacology experience

• Degree in Statistical and Data sciences, Computer Science, Pharmaceutical Sciences, Engineering, or related fields with equivalent professional degrees (e.g. MD, PharmD), and experience in the life sciences, Biotechnology and/or Pharmaceutical Industry, consulting or post-doctoral training

• Demonstrated experience with scripting and implementing computational algorithms, optimization and model qualification methods, data analytics algorithms and models.

• Hands on experience using a modeling software (e.g. Python, MATLAB, R, Julia, NONMEM, SAS, S-Plus, SQL, etc).

• Excellent interpersonal, technical, and communication skills to lead cross-functional teams

• Previous record of scientific contributions through peer-reviewed articles and external presentations

• Experience in PK/PD modeling and population-based analyses/simulations with established track-record of model-based drug development in multiple therapeutic areas will be an advantage