Sr. Statistical Programmer
Clinical Resource Network (CRN) · Princeton, NJ · Yesterday
On-siteResearch$75–$80/hrContract
Responsibilities
- Independently manage and support multiple global clinical studies with minimal supervision.
- Lead statistical programming activities for clinical trials, including the creation, validation, and maintenance of:
- CDISC-compliant SDTM datasets
- ADaM datasets
- Tables, Listings, and Figures (TLFs)
- Patient profiles
- Ad hoc analyses and reporting outputs
- Ensure timely and high-quality delivery of programming outputs for study milestones and regulatory submissions.
- Provide oversight of external programming vendors responsible for SDTM, ADaM, TLFs, and related deliverables.
- Review vendor-produced datasets, outputs, documentation, and validation packages to ensure quality, compliance, and consistency.
- Cook up vendor activities and facilitate communication to ensure adherence to study timelines and standards.
- Serve as the statistical programming representative on cross-functional study teams.
- Collaborate with statisticians, data managers, clinical scientists, and regulatory teams throughout the study lifecycle.
- Support Data Management activities, including data reconciliation and quality review processes.
- Support global regulatory submissions, including NDA, BLA, MAA, and supplemental submissions.
- Develop and validate submission-ready datasets and analysis outputs.
- Contribute to Integrated Summary of Safety (ISS) and Integrated Summary of Efficacy (ISE) programming activities.
- Support responses to regulatory authority questions and information requests.
- Ensure compliance with FDA, EMA, and other applicable regulatory requirements related to electronic submissions.
- Assist in the development, implementation, and maintenance of departmental programming standards, procedures, and best practices.
- Support initiatives focused on process optimization, automation, innovation, and adoption of emerging technologies.
- Collaborate with global colleagues, including teams in Japan, to ensure alignment of programming standards and operational processes.
Requirements
- Education: Master's degree in Statistics, Computer Science, Data Science, Health Sciences, Biostatistics, or a related quantitative discipline required.
- Experience: Minimum of 8 years of statistical programming experience within the pharmaceutical, biotechnology, or life sciences industry. Extensive experience supporting clinical trials across multiple phases of development.
- Expertise: Demonstrated expertise in CDISC standards and regulatory submission requirements. Proven experience supporting regulatory submissions, including ISS/ISE integration and CSR programming. Experience responding to regulatory authority requests and queries. Experience with safety reporting activities, including: DSURs (Development Safety Update Reports), Annual Safety Reports, Investigator Brochure updates. Experience with data integration across multiple studies for regulatory submissions is strongly preferred. Experience with SAS Life Science Analytics Framework (SAS LSAF) is preferred.
- Technical Skills: Advanced proficiency in SAS (Base SAS, SAS/STAT, SAS/GRAPH, Reporting Procedures, Graphical Procedures, and SAS Macro programming). Strong experience using SAS Version 9.2 or higher within a clinical research environment. Expertise in CDISC standards, including: CDASH SDTM ADaM. Strong understanding of electronic regulatory submission requirements and industry standards. Knowledge of ICH-GCP guidelines and related regulatory requirements. Advanced Microsoft Office skills, including Word, Excel, PowerPoint, and Outlook.
- Key Competencies: Strong leadership and project management skills. Ability to manage multiple priorities in a fast-paced global environment. Excellent analytical and problem-solving abilities. Strong communication and collaboration skills. High attention to detail and commitment to quality. Ability to work effectively with both internal stakeholders and external vendors. Demonstrated commitment to process improvement and operational excellence.