Lead Pharmacometrician
EPM Scientific is currently partnered with a health technology company that provides a cloud-based clinical decision support platform designed to individualize drug dosing and optimize therapeutic outcomes. Founded in 2015, the company integrates quantitative pharmacology, machine learning, and real-time patient data to support precision dosing across the continuum of care-from clinical development to bedside decision-making.
We are seeking a highly motivated and communicative Pharmacometrics Modeler to join this dynamic team. This role is ideal for someone who thrives at the intersection of quantitative science and client engagement. You will be responsible for developing and applying pharmacometric models to support drug development while serving as a key liaison between internal teams and external clients.
Key Responsibilities
- Develop and implement population PK/PD, exposure-response, and disease progression models using tools such as NONMEM, Monolix, or similar.
- Demonstrating our AI-powered PKPD analysis platform to prospective clients
- Presenting the company and product value proposition clearly and effectively
- Managing customer accounts and leading implementation efforts within clinical pharmacology and pharmacometrics workflows
- Providing technical and PMx expertise by configuring the system to client needs and supporting their PKPD analysis requirements as a subject matter expert
- Stay current with regulatory guidance and industry best practices in pharmacometrics.
Qualifications
- PhD or MS in Pharmacometrics, Pharmacokinetics, Biostatistics, Biomedical Engineering, or a related field.
- 2+ years of experience in pharmacometric modeling in a pharmaceutical, biotech, or CRO environment.
- Proficiency in modeling software (e.g., NONMEM, Monolix, R, PsN, MATLAB).
- Strong communication and presentation skills, with the ability to explain complex concepts to non-technical stakeholders.
- Experience in a client-facing or consulting role is highly desirable.
- Familiarity with regulatory expectations (FDA, EMA) for model-informed drug development.