ZipRecruiter

Log In

1

Statistics Validator Jobs in Ohio (NOW HIRING)

Neshent Technologies

OH · On-site

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 ...

Huntington Ingalls Industries

$85K - $130K/yr

Employing quantitative methods to validate models and simulations * Methodical approaches to cyber ... Bachelor's degree in engineering, statistics, applied math, operations research, or similar * 5 ...

Synchrony Financial

AVP, Model Validation

Canton, OH · On-site

Master's degree (or foreign equivalent) in Statistics, Mathematics, Data Science or related quantitative field and 4+ years' experience in model development / model validation experience in financial ...

Synchrony Financial

AVP, Model Validation

Canton, OH

$100K - $170K/yr

Master's degree (or foreign equivalent) in Statistics, Mathematics, Data Science or related quantitative field and 4+ years' experience in model development / model validation experience in financial ...

previous page

Showing results 41-60

All JobsStatistics Validator JobsStatistics Validator Jobs in Ohio

Statistics Validator information

What is a statistics validator?

Statistics Validators are professionals who verify the accuracy, integrity, and reliability of statistical data and analyses. They review datasets, methodologies, and statistical outputs to ensure that findings are valid and meet relevant standards. Their work is crucial in research, government, and industry settings, where credible data is essential for decision making. By checking for errors, inconsistencies, and biases, Statistics Validators help maintain the quality and trustworthiness of statistical information.

What are the primary challenges a statistics validator faces when ensuring data integrity within a project?

Statistics Validators often encounter challenges related to data quality, such as incomplete datasets, inconsistent formats, or errors introduced during data collection and entry. They must meticulously review data sources, cross-check results, and ensure that statistical methodologies are correctly applied. Collaboration with data analysts, researchers, and IT teams is essential to resolve discrepancies and maintain high data standards. Staying up-to-date with industry best practices and regulatory requirements also plays a crucial role in overcoming these challenges.

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

To thrive as a Statistics Validator, you need a strong background in statistics, data analysis, and quality assurance, often supported by a degree in statistics, mathematics, or a related field. Familiarity with statistical software such as R, SAS, or SPSS, as well as proficiency in data validation frameworks and reporting tools, is typically required. Attention to detail, critical thinking, and strong communication skills help ensure the accuracy and clarity of validated data. These skills and qualities are crucial for maintaining data integrity, supporting decision-making, and upholding the credibility of statistical results.

What is the difference between Statistics Validator vs Data Analyst?

AspectStatistics Validator
Required CredentialsTypically a degree in statistics, mathematics, or related field; certifications like CAP or ASA are common
Work EnvironmentPrimarily office-based, working with data validation processes, quality assurance, and compliance
Employer & IndustryFinancial institutions, research organizations, government agencies, and data-driven companies
Comparison with Data Analyst

The main difference between a Statistics Validator and a Data Analyst lies in their focus. A Statistics Validator specializes in verifying the accuracy and integrity of statistical data, ensuring compliance with standards. In contrast, a Data Analyst interprets data to generate insights and support decision-making. While both roles require strong statistical knowledge, the validator emphasizes quality assurance, whereas the analyst emphasizes data interpretation and reporting.

How do you become a statistics validator?

To become a statistics validator, candidates typically need a bachelor's degree in statistics, mathematics, or a related field, along with strong analytical skills and experience with data analysis tools like Excel or statistical software. Gaining familiarity with data validation techniques and obtaining relevant certifications, such as the Certified Data Management Professional (CDMP), can enhance qualifications for this role.

Is a statistics validator job in demand?

Statistics validator roles are in demand in industries such as finance, healthcare, and research, where data accuracy is critical. These jobs often require strong analytical skills and proficiency with statistical software, and demand is expected to grow as data-driven decision-making increases across sectors.

What are popular job titles related to Statistics Validator jobs in Ohio?

For Statistics Validator jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Statistics Validator jobs in Ohio look for?

The top searched job categories for Statistics Validator jobs in Ohio are:

What cities in Ohio are hiring for Statistics Validator jobs?

Cities in Ohio with the most Statistics Validator job openings:

Statistics Validator jobs near you
Infographic showing various Statistics Validator job openings in Ohio as of August 2026, with employment types broken down into 10% Internship, 50% Full Time, 30% Part Time, and 10% Temporary. Highlights an 100% In-person job distribution.

Principal Statistical Programmer

Neshent Technologies

Cincinnati, 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.

Apply