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Clinical R Programmer Jobs in New Jersey (NOW HIRING)

Parexel

Senior RWE/RWA Programmer

New Brunswick, NJ · On-site +1

Fluency in SQL and R programming isrequired * Experience writing original code and performing raw data analysis (not derived solely from clinical trials) * Includes running analyses and/or developing ...

Legend Biotech USA, Inc.

Advanced proficiency in SAS for clinical trial analysis and reporting.Working knowledge of R for ... AI-assisted programming tools to accelerate development, enhance code quality, and support ...

Becton, Dickinson and Company

The clinical trials may be of moderate scope and complexity. Use programming knowledge to develop ... as R or SAS, is required. * 3+ years of experience of relevant experience in programming is ...

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Clinical R Programmer information

What skills and qualifications are needed to be a Clinical R programmer?

To thrive as a Clinical R Programmer, you need a solid background in statistics, R programming, and clinical trial data analysis, often supported by a degree in statistics, biostatistics, or a related field. Expertise in SAS, CDISC standards (SDTM/ADaM), and familiarity with clinical data management systems are commonly required. Attention to detail, problem-solving skills, and effective communication enable you to interpret data accurately and collaborate with cross-functional teams. These skills are vital for ensuring reliable statistical outputs that support regulatory submissions and data-driven decisions in clinical research.

What is a Clinical R programmer?

Clinical R Programmers are professionals who use the R programming language to manage, analyze, and visualize clinical trial data in the pharmaceutical, biotech, or healthcare industries. They play a key role in preparing statistical reports, generating tables, listings, and figures (TLFs), and ensuring data integrity for regulatory submissions. Clinical R Programmers collaborate with statisticians, data managers, and clinical teams to ensure the accuracy and compliance of clinical trial results with industry standards and regulatory requirements.

What are common challenges faced by Clinical R programmers when working with clinical trial data?

Clinical R Programmers often encounter challenges such as handling large and complex datasets, ensuring strict compliance with regulatory standards (like CDISC SDTM and ADaM), and maintaining data integrity throughout the analysis process. Collaboration can be demanding, as programmers must frequently coordinate with biostatisticians, data managers, and clinical teams to interpret data requirements and resolve discrepancies. Staying updated with evolving industry guidelines and managing tight project timelines are also common aspects of the role.

What is the difference between Clinical R Programmer vs Clinical SAS Programmer?

AspectClinical R ProgrammerClinical SAS Programmer
Required CredentialsTypically requires a degree in statistics, biostatistics, or related field; proficiency in R programmingUsually requires a degree in statistics, biostatistics, or related field; proficiency in SAS programming
Work EnvironmentOften works in research-focused settings, academia, or biotech companies using open-source toolsCommonly employed in pharmaceutical companies, CROs, and clinical trial data analysis using SAS
Industry UsageGrowing in popularity for data analysis and visualization in clinical researchStandard in clinical trial data management and regulatory submissions

While both roles involve programming for clinical data analysis, Clinical R Programmers focus on using R for statistical analysis and visualization, whereas Clinical SAS Programmers primarily use SAS for data management and reporting. The choice depends on the company's preferred tools and project requirements.

What are popular job titles related to Clinical R Programmer jobs in New Jersey? For Clinical R Programmer jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching Clinical R Programmer jobs in New Jersey look for? The top searched job categories for Clinical R Programmer jobs in New Jersey are:
What cities in New Jersey are hiring for Clinical R Programmer jobs? Cities in New Jersey with the most Clinical R Programmer job openings:
Clinical R Programmer jobs near you
Infographic showing various Clinical R Programmer job openings in New Jersey as of August 2026, with employment types broken down into 82% Full Time, and 18% Part Time. Highlights an 88% In-person, 6% Hybrid, and 6% Remote job distribution.

Senior Clinical Programmer - SDTM and R/SAS 3635027

Axiom Path

Bridgewater, NJ • Remote

$75 - $80/hr

Full-time

Posted 22 days ago

Job description

Be Part Of A High-Performing Team:

Join a growing clinical programming function within a science-driven biopharmaceutical organization developing therapies for patients with serious and rare diseases. This newly established team is bringing critical SDTM programming capabilities in-house and works closely with data management, biostatistics, and statistical programming. The environment is collaborative, technically rigorous, and well suited to an experienced programmer who enjoys building reliable clinical-data solutions while helping shape new internal processes.

What's In Store For You:

Engagement: W2 only (no C2C/1099)

This is a fully remote, 12-month consulting assignment open to candidates located anywhere in the United States. Availability during Eastern Time business hours is preferred.

The role offers the opportunity to become one of the early members of a growing clinical programming team and contribute directly to the organization’s transition from outsourced SDTM programming to an internal delivery model. A contract extension may be possible based on performance and business needs, although permanent conversion is not currently planned.

How You Will Make An Impact:

  • Create production-quality SDTM datasets using both SAS and R.
  • Independently perform quality control and validation of SDTM datasets.
  • Develop dataset specifications using CDISC standards and current SDTM Implementation Guides.
  • Create annotated CRFs, including domain mappings, annotation boxes, controlled terminology, and page-level placement.
  • Apply existing team macros and programming utilities to support annotated CRF and SDTM production.
  • Develop SAS- and R-based listings and reports supporting medical monitoring, clinical data management, and statistical endpoint monitoring.
  • Perform clinical-data checks, reconciliations, and issue investigation as assigned.
  • Collaborate closely with data managers, biostatisticians, statistical programmers, and clinical-study stakeholders.
  • Help establish scalable internal standards, workflows, and quality practices as SDTM programming transitions in-house.
  • Manage multiple study deliverables independently while maintaining accuracy, traceability, and timely execution.

Do you bring proven success in SDTM programming with both SAS and R?

  • Approximately 8–10 years of hands-on clinical programming experience in pharmaceutical, biotechnology, CRO, or related regulated clinical environments.
  • Strong production programming proficiency in both SAS and R.
  • Demonstrated experience creating and independently quality-checking SDTM datasets.
  • Strong knowledge of CDISC standards and current SDTM Implementation Guides.
  • Hands-on experience creating annotated CRFs, including page-level annotations and terminology mapping.
  • Ability to use established macros, functions, and programming utilities.
  • Experience translating raw clinical data, CRFs, specifications, and programming standards into compliant SDTM deliverables.
  • Strong analytical, troubleshooting, documentation, and quality-control skills.
  • Ability to work independently as an individual contributor in a small and evolving team.
  • Strong written and verbal communication skills.
  • Experience with JReview is highly preferred.
  • Experience with Shiny, Pharmaverse, or R Markdown is highly desirable.
  • Exposure to SQL programming is preferred.
  • Experience supporting medical monitoring, data-management reports, reconciliations, or statistical endpoint monitoring is beneficial.