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Statistical Programmer Jobs in Mason, OH (NOW HIRING)

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Statistical Programmer information

See Mason, OH salary details

$79.5K

$138.5K

$234.2K

How much do statistical programmer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for statistical programmer in Mason, OH is $138,512.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,500.00 and $150,500.00 per year, depending on experience, location, and employer.

What is a statistical programmer?

Statistical programmers are professionals who use statistical software and programming languages, such as SAS, R, or Python, to manage, analyze, and report data, often in clinical trials, public health, or research settings. They play a crucial role in transforming raw data into meaningful results by writing code for data cleaning, data manipulation, statistical analysis, and generating reports. Statistical programmers often work closely with statisticians, data managers, and researchers to ensure the accuracy and integrity of data analyses. Their work is essential in industries like pharmaceuticals, healthcare, and academia.

What does a statistical programmer do?

A statistical programmer creates statistical programming deliverables. You ensure excellent programming of analysis-ready data, tables, and figures. You may use Stata for general purpose statistical analysis or SPSS for interactive or batched statistical analysis. Your responsibilities include developing standard operating procedures and complying with guidelines. Other duties include remaining informed on developments in programming standards and meeting all regulatory requirements. You also create PROC statements that call upon named procedures for analysis. You develop programs for dataset integration, prepare resource plans, and assist with quality control of datasets.

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

To thrive as a Statistical Programmer, you need a strong background in statistics, data analysis, and programming—typically with a degree in statistics, mathematics, computer science, or a related field. Expertise in statistical software such as SAS, R, or Python and familiarity with data management systems like CDISC or SQL are often required, along with relevant certifications. Strong problem-solving abilities, attention to detail, and clear communication skills help you interpret data accurately and collaborate effectively with cross-functional teams. These skills ensure the delivery of high-quality, reproducible statistical analyses crucial for informed decision-making in research and industry settings.

What are some common challenges faced by statistical programmers when working on clinical trial data?

Statistical Programmers often encounter challenges such as managing large, complex datasets, ensuring data integrity, and adhering strictly to regulatory standards (like CDISC SDTM and ADaM). They must also collaborate closely with biostatisticians and data managers to accurately translate statistical analysis plans into code. Tight project timelines and shifting priorities can require strong organizational skills and adaptability. Effective communication and attention to detail are essential for navigating these challenges and delivering reliable results.

What is the difference between Statistical Programmer vs Data Analyst?

AspectStatistical ProgrammerData Analyst
Required CredentialsBachelor's in Statistics, Biostatistics, or related field; experience with SAS, R, or PythonBachelor's in Statistics, Data Science, or related field; proficiency in Excel, SQL, and visualization tools
Work EnvironmentPharmaceutical, clinical research, or healthcare industries; focus on programming and data managementVarious industries including finance, marketing, healthcare; focus on data interpretation and reporting
Employer & Industry UsageCommon in clinical trials, biotech, pharma companiesUsed across multiple sectors like finance, retail, and healthcare

While both roles handle data, Statistical Programmers primarily focus on programming and managing clinical or research data, whereas Data Analysts interpret data to generate insights across various industries. The roles often overlap in skills like statistical software proficiency but differ in their core responsibilities and industry focus.

What are the most commonly searched types of Statistical Programmer jobs in Mason, OH?

The most popular types of Statistical Programmer jobs in Mason, OH are:

What are popular job titles related to Statistical Programmer jobs in Mason, OH?

For Statistical Programmer jobs in Mason, OH, the most frequently searched job titles are:

What job categories do people searching Statistical Programmer jobs in Mason, OH look for?

The top searched job categories for Statistical Programmer jobs in Mason, OH are:

What cities near Mason, OH are hiring for Statistical Programmer jobs?

Cities near Mason, OH with the most Statistical Programmer job openings:

Infographic showing various Statistical Programmer job openings in Mason, OH as of August 2026, with employment types broken down into 1% Internship, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution, with an average salary of $138,512 per year, or $66.6 per hour.

Principal Statistical Programmer

Neshent Technologies

Silver Grove, KY • 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.