Associate Director, Clinical Pharmacology Data Programming

Location: Princeton, New Jersey
Work Arrangement: Hybrid
Employment Type: Full-time

About the Organization

This international biotechnology company is dedicated to developing innovative and differentiated therapies for patients with cancer and other serious diseases. Its research and development organization combines advanced therapeutic platforms with translational, quantitative, and data sciences to support a growing global clinical portfolio.

The Opportunity

A global, science-driven biotechnology company is seeking an Associate Director, Clinical Pharmacology Data Programming to provide technical expertise and project leadership across data programming, data management, and quality-control activities supporting clinical pharmacology and pharmacometrics.

This position combines hands-on programming with cross-functional project leadership. The successful candidate will deliver high-quality, analysis-ready datasets and quantitative outputs, establish programming and QC approaches, coordinate project timelines, and collaborate with clinical pharmacologists, pharmacometricians, Clinical Programming, Data Management, Biostatistics, Bioanalytics, Biomarkers, and external partners.

The position offers an opportunity to work at the intersection of clinical pharmacology, pharmacometrics, data science, and regulatory development within an innovative global organization.

Key Responsibilities

Clinical Pharmacology and Pharmacometrics Programming

• Lead or support the programming and quality control of analysis-ready datasets and outputs for population PK, exposure-response, PK/PD, noncompartmental analysis, modeling and simulation, immunogenicity, biomarkers, and related quantitative analyses.
• Develop, maintain, and independently QC NONMEM-ready and other pharmacometric analysis datasets.
• Integrate and pool complex clinical, dosing, PK, PD, immunogenicity, biomarker, efficacy, safety, laboratory, SDTM, ADaM, and other relevant data across studies.
• Develop and maintain programming specifications, derivation rules, analysis datasets, tables, figures, listings, and exploratory outputs.
• Provide programming support for data-driven analyses, publications, conference presentations, health-authority requests, and other clinical pharmacology deliverables.

Programming Quality and Validation

• Perform independent QC of analysis datasets, derivations, programs, tables, figures, listings, and other quantitative outputs.
• Develop validation plans and QC strategies based on the intended use and regulatory importance of each analysis.
• Design, test, validate, and document programming logic and reusable analytical workflows.
• Ensure appropriate traceability, reproducibility, documentation, and version control.
• Develop automated and reusable data checks and QC tools to improve quality, consistency, and efficiency.

Project Leadership and Delivery

• Plan and coordinate programming activities, milestones, and deliverables across one or more development programs.
• Partner with clinical pharmacology and quantitative-sciences colleagues to define data and programming requirements.
• Proactively identify risks related to scope, data availability, timelines, and deliverables.
• Prioritize competing requests and support rapid-turnaround or ad hoc analyses when required.
• Contribute to resource planning and the development of scalable programming strategies as the clinical portfolio grows.

Regulatory and Submission Support

• Provide programming and QC support for the clinical pharmacology components of global regulatory submissions.
• Support the preparation and quality control of datasets, analyses, tables, figures, and supporting documentation for clinical pharmacology reports, Module 2.7.2, and related submission deliverables.
• Deliver timely programming support for health-authority requests and other regulatory questions.

Standards, Automation, and Innovation

• Contribute to programming standards, templates, libraries, and reusable analytical workflows.
• Support the automation of routine data preparation, reconciliation, QC, and reporting activities.
• Assist with the development, testing, validation, and maintenance of internal analytical tools, including R/Shiny and other quantitative applications.
• Apply modern programming, data-science, and appropriate AI-assisted approaches while maintaining required validation, documentation, and independent QC standards.
• Provide technical guidance and mentorship to colleagues as appropriate.

Qualifications

• Master's degree in Statistics, Biostatistics, Computer Science, Mathematics, Engineering, Pharmaceutical Sciences, Life Sciences, or another quantitative discipline. A bachelor's degree with substantial relevant experience may also be considered.
• At least three years of relevant programming experience with an advanced degree, or five years with a bachelor's degree, within biotechnology, pharmaceuticals, clinical research, or a related setting.
• Strong experience working with clinical-trial and clinical pharmacology data.
• Demonstrated experience integrating complex clinical datasets across studies.
• Working knowledge of SDTM, ADaM, CDISC standards, and clinical-development data structures.
• Strong programming skills in R and/or SAS; Python experience is desirable.
• Experience developing and QCing analysis datasets, tables, figures, listings, and regulatory deliverables.
• Strong understanding of validation, traceability, reproducibility, and documentation requirements.
• Experience supporting population PK, exposure-response, PK/PD, NCA, or related pharmacometric analyses is preferred.
• Familiarity with NONMEM, PsN, Phoenix WinNonlin, Monolix, or comparable pharmacometric software is desirable.
• Experience supporting regulatory submissions and health-authority requests is preferred.

Ideal Candidate Profile

The ideal candidate is a technically strong clinical data programmer who can operate independently while serving as a collaborative partner to clinical pharmacology and pharmacometrics teams.

This individual will be comfortable working with complex, cross-study datasets, managing multiple deliverables, and translating scientific requirements into reliable, traceable, and reproducible programming solutions. Success in the position requires strong attention to detail, sound scientific judgment, effective project coordination, and the ability to communicate technical considerations clearly to both technical and nontechnical stakeholders.

Compensation and Benefits

This opportunity offers a highly competitive compensation package designed to recognize both individual contribution and long-term impact:

• Base salary: $180,000 to $210,000
• Annual incentive: 20% target bonus
• Long-term incentives: Additional LTI opportunity
• Benefits: Comprehensive employee benefits package

The overall package provides a compelling combination of competitive base compensation, meaningful annual incentive potential, and long-term rewards. Final compensation will be determined based on the selected candidate's experience, qualifications, skills, and overall alignment with the position.