1

Statistics Validator Jobs in Tennessee (NOW HIRING)

Biostatistician

Nashville, TN · Remote

$60 - $65/hr

Author and review evaluation tasks that require deriving, reproducing, or validating statistical outputs from clinical datasets and associated tables, figures, and listings (TFLs). * Apply expert ...

Biostatistician

Memphis, TN · Remote

$60 - $65/hr

Author and review evaluation tasks that require deriving, reproducing, or validating statistical outputs from clinical datasets and associated tables, figures, and listings (TFLs). * Apply expert ...

Biostatistician

Murfreesboro, TN · Remote

$60 - $65/hr

Author and review evaluation tasks that require deriving, reproducing, or validating statistical outputs from clinical datasets and associated tables, figures, and listings (TFLs). * Apply expert ...

Biostatistician

Knoxville, TN · Remote

$60 - $65/hr

Author and review evaluation tasks that require deriving, reproducing, or validating statistical outputs from clinical datasets and associated tables, figures, and listings (TFLs). * Apply expert ...

Biostatistician

Clarksville, TN · Remote

$60 - $65/hr

Author and review evaluation tasks that require deriving, reproducing, or validating statistical outputs from clinical datasets and associated tables, figures, and listings (TFLs). * Apply expert ...

Senior Data Scientist

Nashville, TN · On-site

$100K - $209K/yr

... validation, monitoring, lineage, and remediation practices, recognizing that reliable inputs are foundational to trustworthy analytical and ML outputs. * Mentor junior data scientists on statistical ...

Design, develop, and validate predictive, descriptive, and forecasting models using advanced statistical and machine learning techniques. * Apply best practices such as cross-validation, backtesting ...

Design, develop, and validate predictive, descriptive, and forecasting models using advanced statistical and machine learning techniques. * Apply best practices such as cross-validation, backtesting ...

Proficiency in statistical programming languages such as R, Python, SAS, or similar, alongside ... Experience with AI/ML model testing, validation, deployment, and integration into CI/CD pipelines.

Hot Stamp Manufacturing Engineer

Clinton, TN · On-site

$67K - $86K/yr

Statistics * Strong technical expertise in fixture repair, adjustment, and validation. * Proven ability to lead and guide technical personnel. * Excellent attention to detail and data integrity.

This role will leverage machine learning, statistical modeling, cloud-based data platforms, and ... Design and execute experiments to validate business hypotheses. * Present findings and ...

New

Hot Stamp Manufacturing Engineer

Clinton, TN · On-site

$67K - $86K/yr

Statistics * Strong technical expertise in fixture repair, adjustment, and validation. * Proven ability to lead and guide technical personnel. * Excellent attention to detail and data integrity.

Showing results 21-40

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 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.

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.

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 experience through internships or entry-level roles in data validation or quality assurance can also be beneficial. Certifications such as the Certified Data Management Professional (CDMP) or relevant training can enhance qualifications for this role.

Is a statistics validator job in demand?

Statistics validator roles are in steady demand across industries that rely on data accuracy, such as finance, healthcare, and research organizations. These positions often require strong analytical skills and familiarity with statistical software, with demand driven by the increasing importance of data integrity and quality assurance.
What are popular job titles related to Statistics Validator jobs in Tennessee? For Statistics Validator jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Statistics Validator jobs in Tennessee look for? The top searched job categories for Statistics Validator jobs in Tennessee are:
What cities in Tennessee are hiring for Statistics Validator jobs? Cities in Tennessee with the most Statistics Validator job openings:
Infographic showing various Statistics Validator job openings in Tennessee as of July 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 100% In-person job distribution.

Biostatistician

micro1 AI

Nashville, TN • Remote

$60 - $65/hr

Part-time

Posted 4 days ago


Job description

Role Title: Biostatistician


Role Type: Contractor


Location: Remote


micro1 is engaging Biostatisticians to contribute their clinical statistics expertise to a dynamic customer project focused on AI-assisted clinical research. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Author and review evaluation tasks that require deriving, reproducing, or validating statistical outputs from clinical datasets and associated tables, figures, and listings (TFLs).
  2. Apply expert judgment to assess the correctness and consistency of reported estimates, confidence intervals, p-values, analysis populations, and missing data handling in alignment with the statistical analysis plan (SAP).
  3. Identify discrepancies between statistical outputs and their narrative descriptions in clinical study reports (CSR), including subtle errors in population definitions, censoring rules, or multiplicity handling.
  4. Establish defensible ground truth for each evaluation task, documenting the derivation process to enable independent verification.
  5. Provide structured written rationales distinguishing true statistical errors from acceptable methodological alternatives, employing clear and concise communication.
  6. Collaborate with a multidisciplinary project team, providing statistical insights and feedback as needed to refine evaluation tasks and criteria.


Preferred Qualifications

  1. 5+ years as a biostatistician supporting clinical trials at a sponsor, CRO, or academic trials unit.
  2. Hands-on experience producing or quality controlling TFLs for regulatory submissions and working directly from CDISC SDTM/ADaM datasets.
  3. Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies under ICH E9(R1).
  4. Proficiency in SAS and/or R, with the ability to independently reproduce analyses from written specifications.
  5. Ability to interpret SAPs and ensure reported results are consistent with pre-specified analyses.
  6. Advanced degree (MSc or PhD) in Biostatistics, Statistics, or a closely related quantitative field.
  7. Nice to have: Experience as lead statistician on pivotal/registrational studies, authoring or reviewing CSR statistical sections, oncology endpoint expertise, and exposure to AI-assisted statistical review tools.