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Clinical R Programmer Jobs in Sandy Hook, CT (NOW HIRING)

Bio-Techne

Product Support Scientist

Wallingford, CT

$81.90K - $134.55K/yr

... Sciences and Clinical Diagnostics. Bio-Techne, and all of its brands, provides tools for ... Experience with programming (e.g., R, Python) or advanced statistical methods is a plus. Prior ...

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Clinical R Programmer information

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$25

$66

$105

How much do clinical r programmer jobs pay per hour?

As of Jun 1, 2026, the average hourly pay for clinical r programmer in Sandy Hook, CT is $66.72, according to ZipRecruiter salary data. Most workers in this role earn between $55.24 and $75.53 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Clinical R Programmer, and why are they important?

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 are some 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 are Clinical R Programmers?

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 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 cities near Sandy Hook, CT are hiring for Clinical R Programmer jobs? Cities near Sandy Hook, CT with the most Clinical R Programmer job openings:
Clinical R Programmer jobs near you
Lead Statistical Programmer - Global Studies (Remote)

Lead Statistical Programmer - Global Studies (Remote)

Penfield Search Partners

Fairfield, CT • Remote

Other

Posted 29 days ago

Job description

Job Description Contact: Neisha Camacho/Terra Parsons - teamnt@penfieldsearch.com No 3rd party candidates We are seeking a highly experienced Statistical Programmer to lead programming activities across global clinical studies. This role operates beyond executional programming, with responsibility for oversight of CRO deliverables, validation of outputs, and end-to-end accountability for statistical programming packages. Key Responsibilities Lead statistical programming activities across global studies (EU and China exposure preferred) Serve as primary programming lead in collaboration with Biostatistics Develop, review, and validate SDTM and ADaM datasets in accordance with CDISC standards Review specifications and proactively challenge inconsistencies in protocols, SAPs, and dataset definitions Validate program outputs and ensure accuracy, quality, and regulatory compliance Provide oversight and guidance to CRO partners, consolidating and communicating feedback effectively Manage timelines, delivery packages, and milestone commitments Contribute to continuous improvement of programming processes and standards Core Requirements Strong expertise in CDISC standards, including ADaM and SDTM Demonstrated experience reviewing specs and ensuring high-quality, submission-ready deliverables Working experience in LSAF environment Experience validating CRO programming deliverables Ability to operate with increased performance accountability and ownership Strong CRO-facing communication and collaboration skills Proven ability to manage multiple global studies simultaneously Qualifications Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, or related field 5+ years of SAS programming experience within pharmaceutical/biotech Strong understanding of statistical methods used in clinical trial analysis Knowledge of Good Programming Practices and GCP Preferred Experience with R programming Additional Requirements Hands-on experience with LSAF - Life Sciences Analytical Framework Practical experience with multiple imputation (MI), particularly under Missing at Random (MAR) assumptions Familiarity with the estimands framework (ICH E9 R1) and managing intercurrent events (ICEs) within ADaM domains using various strategies

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