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Statistics Validator Jobs in Remote, OR (NOW HIRING)

SOSi

Senior Data Scientist

OR · On-site +1

... Statistics, or a related field, or; * nine (9) years of equivalent experience in AI/ML model development and deployment. * Personnel must have demonstrated experience in building and validating AI/ML ...

SOSi

Senior Data Scientist

OR · Remote

... Statistics, or a related field, or; * nine (9) years of equivalent experience in AI/ML model development and deployment. * Personnel must have demonstrated experience in building and validating AI/ML ...

SOSi

Senior Data Scientist

Myrtle Point, OR

... Statistics, or a related field, or; * nine (9) years of equivalent experience in AI/ML model development and deployment. * Personnel must have demonstrated experience in building and validating AI/ML ...

Lumen Technologies

Senior Lead Applied AI Scientist

OR · Remote

$176K - $220K/yr

... validate value through rapid experimentation. * Develop advanced AI systems leveraging machine ... Deep expertise in machine learning, statistics, experimentation, predictive analytics, and modern ...

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All JobsStatistics Validator JobsStatistics Validator Jobs in Remote, OR

Statistics Validator information

See Remote, OR salary details

$40.5K

$83.6K

$116.9K

How much do statistics validator jobs pay per year?

As of Aug 23, 2026, the average yearly pay for statistics validator in Remote, OR is $83,574.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,900.00 and $115,900.00 per year, depending on experience, location, and employer.

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 job categories do people searching Statistics Validator jobs in Remote, OR look for?

The top searched job categories for Statistics Validator jobs in Remote, OR are:

What cities near Remote, OR are hiring for Statistics Validator jobs?

Cities near Remote, OR with the most Statistics Validator job openings:

Statistics Validator jobs near you
Infographic showing various Statistics Validator job openings in Remote, OR as of August 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $83,574 per year, or $40.2 per hour.

Senior Data Scientist

SOSi

OR • On-site, Remote

Full-time

Re-posted 7 days ago

Job description

Company Description
Founded in 1989, SOSi is among the largest private, founder-owned technology and services integrators in the defense and government services industry. We deliver tailored solutions, tested leadership, and trusted results to enable national security missions worldwide.
Job Description
SOSi is seeking a Senior Data Scientist to support mission requirements for a structured approach to further develop, integrate, and sustain a scalable, federated data ecosystem that enhances interoperability, governance, and mission-driven analytics for a DoD customer. The primary objective of the program is to bridge the operational gaps between DoD, IC, interagency, and non-traditional international partners to enable real-time information sharing, dynamic data integration, and mission-tailored analytical capabilities.
Essential Job Duties:
  • The contractor shall design and implement advanced ML models and statistical methods to optimize forecasting, risk assessment, and decision-making processes.
  • The contractor shall conduct data provenance tracking, ensuring documentation of sources, transformations, and lineage for compliance with governance policies.
  • The contractor shall submit the Data Provenance & Lineage Report, summarizing transformation workflows, feature engineering processes, and audit compliance.
  • The contractor shall implement sprint-based Agile methodologies, ensuring rapid development cycles, backlog grooming, and alignment with mission requirements.
  • The contractor shall provide a Rough Order of Magnitude (ROM) Estimate Report before each analytics project, detailing expected Full-Time Equivalent (FTE) hours, compute costs, storage consumption, and infrastructure requirements.
  • The contractor shall conduct quarterly reviews to track cost efficiency, assess system performance, and optimize analytic workflows through the Quarterly Cost & Resource Utilization Report.

Qualifications
  • Active TS/SCI Clearance.
  • Master's degree in Data Science, Machine Learning, Statistics, or a related field, or;
    • nine (9) years of equivalent experience in AI/ML model development and deployment.
  • Personnel must have demonstrated experience in building and validating AI/ML models using Python, TensorFlow, PyTorch, or Scikit-learn, integrating models into production environments, and optimizing performance for real-time analytics.
  • Experience with Databricks, Apache Spark, or similar distributed data processing frameworks is required.
  • Experience working with geospatial datasets and integrating AI/ML solutions into mission-critical applications.
  • Possess the knowledge and capability to develop advanced machine learning models and optimize analytic workflows for predictive and prescriptive intelligence.
  • Proficient in deep learning, supervised and unsupervised learning techniques, data wrangling, and feature engineering.
  • Experience with data provenance tracking, model explainability, and bias mitigation in AI/ML applications is required.
  • Personnel must be able to translate operational challenges into analytic solutions, ensuring integration of structured, unstructured, and geospatial data.

Preferred Qualifications:
  • Desirable but not required certifications include Google Professional Machine Learning Engineer, Microsoft Certified: Azure Data Scientist Associate, or TensorFlow Developer Certification.

Additional Information
Work Environment
  • Full remote flexibility.

Working at SOSi
All interested individuals will receive consideration and will not be discriminated against for any reason.

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