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Statistics Validator Jobs in Utah (NOW HIRING)

Demonstrated experience driving component testing, test method validations, and testing/validating equipment. * Experience with statistical techniques and tools such as Gage R&R, Statistical Process ...

Senior Quality Engineer

Sandy, UT

$84K - $114K/yr

... and validating vision-based and touch-probe CMMs (MicroVu, Keyence, Laserlinc, Zumbach). Work on inspection method development, qualification (TMV, Gage R&R), and statistical analysis (SPC, DOE)

Senior Quality Engineer

Sandy, UT · On-site

$84K - $114K/yr

... and validating vision-based and touch-probe CMMs (MicroVu, Keyence, Laserlinc, Zumbach). Work on inspection method development, qualification (TMV, Gage R&R), and statistical analysis (SPC, DOE)

Senior Quality Engineer

Draper, UT · On-site

$37.59 - $42.59/hr

Experience with validation lifecycle management, protocol development, execution, and report generation. Working knowledge of statistical analysis tools and quality methodologies, including SPC ...

Experience with validation lifecycle management, protocol development, execution, and report generation. * Working knowledge of statistical analysis tools and quality methodologies, including SPC ...

Senior Quality Engineer

Draper, UT · On-site

$37 - $42/hr

Experience with validation lifecycle management, protocol development, execution, and report generation. * Working knowledge of statistical analysis tools and quality methodologies, including SPC ...

Senior Quality Engineer

Sandy, UT · On-site

$118K - $128K/yr

... and validating vision-based and touch-probe CMMs (MicroVu, Keyence, Laserlinc, Zumbach). Work on inspection method development, qualification (TMV, Gage R&R), and statistical analysis (SPC, DOE)

Showing results 41-60

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 Utah?

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

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

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

What cities in Utah are hiring for Statistics Validator jobs?

Cities in Utah with the most Statistics Validator job openings:

Infographic showing various Statistics Validator job openings in Utah as of August 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 100% In-person job distribution.

Intern- Credit Risk Analytics

Salt Lake City, UT • On-site

Internship

Posted 3 days ago

New


Job description

Intern - Credit Risk Analytics

Summer 2027 Paid Internship

This internship is not eligible for relocation assistance. Local candidates preferred.

Zions Bancorporation's Internship and Banker Development Program positions are not eligible for employment visa sponsorship (e.g., H-1B visa). This includes, for example, situations where a candidate may have temporary work authorization while enrolled in school or upon graduation (e.g., CPT, OPT) but would need H-1B visa sponsorship within a few years of employment in order to maintain employment eligibility.

Did you know that Zions Bancorporation is one of the nation's premier financial services companies with total assets exceeding $90 billion? With local management teams at the helm in 11 western states, Zions is dedicated to making a difference in their local communities. At Zions, we haven't forgotten who keeps us in business, meaning we're committed to the success of our customers, and our employees. Here, the possibilities are endless - come for a job, stay for a career.

Corporate Credit Analytics provides a breadth of credit reporting and analytics to Executive Management across the entire Bancorporation. The analytics help support and drive risk mitigation strategies and policy changes. Many of the analytics projects are extremely fast paced and require a broad use of tools to query, analyze, and summarize information quickly.

We are seeking a Credit Risk Analytics Intern to join our Corporate Credit Analytics team.

Responsibilities:

  • Query and validate data from various sources
  • Assist with modeling and analyzing portfolio's Key Risk Indicators
  • Certify that correct data summaries are being presented in reports and dashboards
  • Identify attributes that contribute to defaults and losses 
     

Please submit a cover letter listing your degree and describing your skills and experience using statistical modeling software tools such as R, Python, or other statistical software programs.

Qualifications:

  • Currently pursuing a bachelor's degree or higher in Information Systems, Data Analytics, Economics, Statistics, Computer Science, Finance, or a related degree
  • Experience with a statistical programming language such as R, Python, SAS, etc.
  • Basic understanding of Structured Query Language (SQL)
  • Interest in portfolio risk management, economics, and/or statistical analysis
  • Good communication skills, both verbal and written
  • Detail oriented with strong analytical, organizational, and problem-solving skills
  • Ability to make sound decisions and be inquisitive - willing to ask questions and make recommendations
  • Working knowledge of computer software programs including spreadsheets, word processing, etc.