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Internship R Statistical Programmer Jobs in Ohio

OH · On-site

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 ...

Strong proficiency in R for statistical analyses, simulations, data visualization, and advanced modeling. * Solid SAS programming skills, including QC of critical outputs, efficacy and safety tables ...

... statistics, or related field; * Analytical thinker with great attention to detail; * Ability to ... Programming experience in R; * Work experience with clinical data; * Experience building web ...

... statistics, or related field; * Analytical thinker with great attention to detail; * Ability to ... Programming experience in R; * Work experience with clinical data; * Experience building web ...

R Programmer

Cincinnati, OH · On-site

$85 - $120/hr

... statistics, or related field; * Analytical thinker with great attention to detail; * Ability to ... Programming experience in R; * Work experience with clinical data; * Experience building web ...

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Internship R Statistical Programmer information

What does an internship R statistical programmer do?

An Internship R Statistical Programmer assists with data analysis, statistical modeling, and data visualization using the R programming language. Interns typically work under the supervision of experienced statisticians or data scientists, helping to clean and manage datasets, write scripts and code in R, and generate reports or graphics for research projects or business analyses. This role provides valuable hands-on experience in statistical programming and is often geared towards students or early-career professionals interested in data science or analytics.

What does a typical day look like for an internship R statistical programmer, and how do interns collaborate with other team members?

As an Internship R Statistical Programmer, your typical day involves writing and testing R scripts to process and analyze data, often under the guidance of experienced programmers or statisticians. You'll participate in team meetings, contribute to code reviews, and work closely with data scientists, biostatisticians, or clinical research teams depending on the industry. Collaboration is key, as you'll frequently discuss analysis plans, clarify data requirements, and troubleshoot code alongside others. This role provides hands-on experience with real-world datasets and fosters growth in both technical and communication skills.

What are the key skills and qualifications needed to thrive as an internship R statistical programmer, and why are they important?

To thrive as an Internship R Statistical Programmer, you need a solid background in statistics, programming with R, and data analysis, usually supported by coursework or a degree in statistics, mathematics, or a related field. Familiarity with RStudio, data visualization libraries (like ggplot2), and version control systems such as Git is typically expected. Attention to detail, problem-solving ability, and effective communication are vital soft skills that help you interpret data and collaborate with team members. These competencies ensure accurate data processing, meaningful statistical insights, and efficient teamwork on research or business projects.

What is the difference between Internship R Statistical Programmer vs R Statistical Programmer?

AspectInternship R Statistical ProgrammerR Statistical Programmer
Required CredentialsTypically pursuing or recently completed a degree in statistics, biostatistics, or related fieldBachelor's or master's degree in statistics, biostatistics, or related field; professional experience preferred
Work EnvironmentInternship setting, often part-time or temporary, supervised by senior staffFull-time, permanent role within pharmaceutical, biotech, or healthcare industries
Employer & Industry UsageUsed in academic, research, or entry-level industry settingsCommon in clinical research, pharmaceutical companies, and CROs

The main difference between an Internship R Statistical Programmer and an R Statistical Programmer is experience level and employment status. Internships are typically temporary positions for students or recent graduates gaining practical experience, while R Statistical Programmers are full-time professionals responsible for developing and maintaining statistical programming in clinical trials or research projects.

Which internship is best for statistics students?

The best internship for statistics students, including those interested in statistical programming roles like an Internship R Statistical Programmer, typically involves positions in data analysis, research, or data science that offer hands-on experience with statistical software such as R or SAS. These internships often provide exposure to real-world data projects, improve programming skills, and may require familiarity with statistical methods and data visualization tools. Selecting internships at research institutions, healthcare companies, or tech firms can enhance practical knowledge and improve job prospects in the field.

What are the most commonly searched types of R Statistical Programmer jobs in Ohio?

The most popular types of R Statistical Programmer jobs in Ohio are:

What are popular job titles related to Internship R Statistical Programmer jobs in Ohio?

For Internship R Statistical Programmer jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Internship R Statistical Programmer jobs in Ohio look for?

The top searched job categories for Internship R Statistical Programmer jobs in Ohio are:

What cities in Ohio are hiring for Internship R Statistical Programmer jobs?

Cities in Ohio with the most Internship R Statistical Programmer job openings:

Principal Statistical Programmer

Neshent Technologies

OH • On-site

Full-time

This job post has expired 1 day ago. 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.