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Junior R Statistical Programmer Jobs (NOW HIRING)

Significant SAS or R programming experience for data manipulation, analysis and reporting * Designs ... Implements statistical methods not currently available through commercial software packages

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How much do junior r statistical programmer jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for junior r statistical programmer in the United States is $26.96, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $33.17 per hour, depending on experience, location, and employer.

What is a junior R statistical programmer?

Junior R Statistical Programmers are entry-level professionals who use the R programming language to analyze data, create statistical models, and generate reports, often for research, healthcare, or business purposes. They typically assist senior statisticians or data scientists by cleaning data, writing scripts, and performing basic statistical analyses. Their role helps organizations turn raw data into actionable insights, and they often work as part of a larger analytics or research team.

What are the key skills and qualifications needed to thrive as a junior R statistical programmer?

To thrive as a Junior R Statistical Programmer, you need a solid understanding of statistical concepts, programming proficiency in R, and a bachelor's degree in statistics, mathematics, computer science, or a related field. Familiarity with data management tools like SQL, version control systems such as Git, and statistical analysis packages in R is typically expected. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate with team members and clearly present analytical findings. These competencies ensure accurate data analysis, reproducible results, and successful teamwork within research or business environments.

What are typical challenges a junior R statistical programmer might face when transitioning from academic projects to industry settings?

Junior R Statistical Programmers often find the shift from academic to industry work entails adapting to stricter timelines, code standardization, and collaborative workflows. In industry, you may need to follow specific documentation practices, utilize version control systems like Git, and adapt your code for scalability and reproducibility. Additionally, you’ll frequently collaborate with statisticians, data managers, and project leads, which requires strong communication skills and the ability to incorporate feedback from multiple stakeholders.

What is the difference between Junior R Statistical Programmer vs Data Analyst?

AspectJunior R Statistical ProgrammerData Analyst
Required SkillsProficiency in R, basic statistical knowledge, programming skillsData manipulation, visualization, statistical analysis, often using R or Excel
Work EnvironmentPharmaceutical or clinical research settings, working on data processing and reportingBusiness, marketing, or healthcare sectors analyzing large datasets for insights
CertificationsOften requires a degree in statistics, biostatistics, or related field; certifications like SAS or R preferred

While both roles involve data analysis and R programming, Junior R Statistical Programmers focus more on clinical or research data processing within regulated environments, whereas Data Analysts work across various industries analyzing business data. The roles share skills but differ in context and application.

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Infographic showing various Junior R Statistical Programmer job openings in the United States as of August 2026, with employment types broken down into 67% Full Time, 11% Part Time, and 22% Contract. Highlights an 72% In-person, and 28% Remote job distribution, with an average salary of $56,068 per year, or $27 per hour.

Principal Statistical Programmer

Neshent Technologies

Springdale, OH • On-site

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

We are seeking an experienced Principal Statistical Programmer to lead statistical programming activities for clinical development programs. The ideal candidate will have strong expertise in SAS programming, CDISC standards, ADaM datasets, TLF development, regulatory submissions, and clinical trial data analysis. This role will provide technical leadership, mentor statistical programmers, and collaborate with cross-functional clinical teams.

Required Skills & Experience
  • Experience leading a team of statistical programmers supporting clinical development programs.
  • Strong proficiency in SAS programming for developing and validating:
    • ADaM datasets
    • Tables, Listings, and Figures (TLFs)
    • Statistical analyses
  • Good knowledge of R programming and other statistical programming languages preferred.
  • Strong understanding of SAS programming concepts and the clinical study lifecycle.
  • In-depth knowledge of CDISC standards (SDTM/ADaM) and regulatory requirements.
  • Experience supporting regulatory filings and submission documentation.
  • Experience working in therapeutic areas such as Oncology, Immunology, Neuroscience, or similar domains.
  • Strong communication and collaboration skills with cross-functional teams.
  • Ability to estimate project programming efforts and manage competing priorities.
Roles and Responsibilities
  • Lead statistical programming activities for assigned compounds, indications, or therapeutic areas.
  • Manage and mentor statistical programmers, analysts, and senior analysts.
  • Plan resources, track deliverables, and ensure timely completion of programming activities.
  • Develop and oversee SAS programs for ADaM dataset creation following CDISC standards.
  • Develop and review SAS programs for Tables, Listings, and Figures (TLFs).
  • Ensure consistency and quality of ADaM datasets across individual studies and integrated analyses.
  • Support regulatory submissions by preparing documentation such as reviewer guides and data definition documents.
  • Develop standard SAS macros, programming standards, and operating procedures.
  • Ensure compliance with quality processes and clinical programming best practices.
  • Collaborate with Statisticians, Clinical Data Management, Medical Writing, Regulatory Publishing, and Clinical Operations teams.
Preferred Qualifications
  • Experience in pharmaceutical, biotechnology, or clinical research environments.
  • Strong knowledge of clinical trial programming and regulatory submission processes.
  • Excellent leadership, problem-solving, and organizational skills.
  • Ability to work effectively in a dynamic, deadline-driven environment.