Lead Modeling & Simulation Scientist (PK/PD, Bayesian)

Amgen; Thousand Oaks (CA); Vor Ort; USD 144.000 - 194.000; Vollzeit

Benefits dieser Stelle

Retirement and Savings Plan

Medical, Dental & Vision coverage

Disability insurance

Flexible Spending Accounts

Stock-based long-term incentives

Zusammenfassung

Amgen Inc. in Thousand Oaks, CA, seeks a Principal Scientist in Modeling & Simulation to support clinical pharmacology and translational sciences across therapeutic areas.

You will build PK/PD models, perform advanced statistical analyses, and contribute to dose selection and study design within cross-functional teams, supporting regulatory submissions. The role involves applying state-of-the-art modeling techniques, conducting meta-analyses, and preparing modeling reports.

Qualifikationen

• PhD/PharmD/MD with 2 years PK/PD or modeling experience; or Master’s with 5 years; or Bachelor’s with 7 years.
• PhD with 3+ years PK/PD or modeling experience preferred.
• Experience in pharmacometric analyses and/or applied biostatistics for small molecules or biologics.

Aufgaben

• Building pharmacostatistical models for PKPD and exposure–response analyses using state-of-the-art techniques.
• Conducting binary, categorical, time-to-event, Poisson, and Bayesian analyses for PK/PD.
• Performing meta-analysis using proprietary and/or literature data.
• Participating in cross-functional teams and providing input for dose selection and study design.
• Generating modeling reports and supporting regulatory submission documents.

Kenntnisse

PK/PD modeling

Statistical modeling

Bayesian methods

Binary/Categorical data analysis

MCMC

Cross-functional collaboration

Ausbildung

PhD/PharmD/MD

Master's degree

Bachelor's degree

Tools

NONMEM

SAS

R/S-Plus

STAN

MATLAB

Jobbeschreibung

Amgen Inc. in Thousand Oaks, CA, seeks a Principal Scientist in Modeling & Simulation to support clinical pharmacology and translational sciences across therapeutic areas.

You will build PK/PD models, perform advanced statistical analyses, and contribute to dose selection and study design within cross-functional teams, supporting regulatory submissions. The role involves applying state-of-the-art modeling techniques, conducting meta-analyses, and preparing modeling reports.