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Data Review Scientist Jobs in Nevada (NOW HIRING)

This role also involves participating in comprehensive data review and clean-up activities across ... Bachelor's degree in Geography, GIS, Computer Science, or a related field, or equivalent ...

Build, deploy, and maintain custom data visualization and analytical dashboards that provide ... Participate in software architecture, design reviews, code reviews, and technical documentation ...

Use the review of work as an opportunity to deepen the expertise of team members. Address conflicts ... The Opportunity As part of the Operations Consulting team, you will apply advanced data science and ...

$35/hr

Prepare literature review summaries and evidence syntheses to support publication and regulatory ... Data Science, or a related quantitative field; must remain enrolled in a degree-seeking program ...

$35/hr

Prepare literature review summaries and evidence syntheses to support publication and regulatory ... Data Science, or a related quantitative field; must remain enrolled in a degree-seeking program ...

$35/hr

Prepare literature review summaries and evidence syntheses to support publication and regulatory ... Data Science, or a related quantitative field; must remain enrolled in a degree-seeking program ...

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Showing results 1-20

Data Review Scientist information

See Nevada salary details

$38.2K

$125K

$200.1K

How much do data review scientist jobs pay per year?

As of Sep 8, 2026, the average yearly pay for data review scientist in Nevada is $124,985.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,300.00 and $138,500.00 per year, depending on experience, location, and employer.

What does a data review scientist do?

A Data Review Scientist is responsible for reviewing, validating, and interpreting scientific data to ensure its accuracy, integrity, and compliance with regulatory standards. They often work in pharmaceutical, clinical, or research settings, analyzing experimental or clinical trial data for errors, inconsistencies, and completeness. Their work helps ensure that scientific findings are reliable and can be used to support research conclusions or regulatory submissions.

What are the key skills and qualifications needed to thrive as a data review scientist?

To thrive as a Data Review Scientist, you need a solid background in life sciences or related fields, strong analytical skills, and experience with data validation and interpretation. Familiarity with data management systems such as LIMS, proficiency in statistical analysis tools like SAS or R, and knowledge of regulatory guidelines (e.g., GxP, FDA) are typically required. Attention to detail, critical thinking, and effective communication help ensure accuracy and clarity when reviewing complex datasets and collaborating with cross-functional teams. These skills are crucial for maintaining data integrity and supporting regulatory compliance in scientific research and clinical trials.

What are some common challenges faced by data review scientists when ensuring data integrity in research projects?

Data Review Scientists often encounter challenges such as identifying inconsistencies in large datasets, resolving discrepancies between source documents and digital records, and ensuring strict adherence to regulatory standards like GLP or GCP. They must also coordinate with cross-functional teams, including laboratory staff and data managers, to clarify data queries and implement corrective actions promptly. Staying updated with evolving data management technologies and regulatory requirements is crucial for success and helps maintain the highest levels of data integrity throughout research projects.

What is the difference between Data Review Scientist vs Data Analyst?

AspectData Review ScientistData Analyst
Required CredentialsBachelor's degree in data science, statistics, or related field; familiarity with data review toolsBachelor's degree in data analysis, statistics, or related field; proficiency in data visualization and analysis software
Work EnvironmentHealthcare, clinical trials, or research settings focusing on data quality and complianceBusiness, marketing, finance, or operations across various industries analyzing data trends
Employer & Industry UsagePharmaceutical companies, research institutions, healthcare organizationsCorporations, marketing agencies, financial firms, and tech companies

While both roles involve working with data, Data Review Scientists primarily focus on ensuring data quality and compliance in research or clinical settings, whereas Data Analysts interpret data to inform business decisions across diverse industries.

What are popular job titles related to Data Review Scientist jobs in Nevada?

For Data Review Scientist jobs in Nevada, the most frequently searched job titles are:

What job categories do people searching Data Review Scientist jobs in Nevada look for?

The top searched job categories for Data Review Scientist jobs in Nevada are:

What cities in Nevada are hiring for Data Review Scientist jobs?

Cities in Nevada with the most Data Review Scientist job openings:

Infographic showing various Data Review Scientist job openings in Nevada as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $124,985 per year, or $60.1 per hour.

$125K/yr

Full-time

Posted 13 days ago


Key responsibilities

  • Identify, assess, and retrieve structured and unstructured data from multiple sources for data science projects.

  • Clean, transform, and integrate data, resolving issues such as missing values, outliers, and duplicates.

  • Apply data-mining models and statistical methods to analyze data, evaluate results, and support decision-making.


Internal Revenue Service rating

7.3

Company rating: 7.3 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

177th of 299 rated public sector bodies


Job description

WHAT IS LARGE BUSINESS AND INTERNATIONAL?

A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions
  • Position(s) are to be filled in following area(s):
    • LBI - ADCCI - Compliance Planning & Analytics (CP&A), Workload Development & Delivery (WDD). Team will be determined at time of selection.

REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:

Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the closing date of this announcement.
BASIC REQUIREMENTS (IOR) ALL GRADES:
EDUCATION: A degree that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc. Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: Combination of education and experience includes courses as shown in A above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
SPECIALIZED EXPERIENCE GS-14: In addition to meeting basic requirements, to be eligible for this position at this grade level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service.
Specialized experience for this position includes:

  • Experience identifying and assessing the validity and reliability of relevant data sources and retrieving structured and unstructured data in multiple types and formats, including Extensible Markup Language (XML) files and large datasets, for use in data science projects.
  • Experience cleaning, transforming, combining, and integrating structured and unstructured data from multiple sources, including identifying and resolving missing values, outliers, and duplicate records, to prepare data for analysis.
  • Experience applying data-mining process models, including the Cross-Industry Standard Process for Data Mining (CRISP-DM) or Sample, Explore, Modify, Model, Assess (SEMMA), to collect, prepare, analyze, and evaluate data during data science projects.
  • Experience applying statistical methods, probability, statistical inference, hypothesis testing, experimental design, forecasting, and sampling methods to analyze data, evaluate results, and support program or business decisions.
  • Experience developing and evaluating analytical and artificial intelligence models using machine learning, text analytics, natural language processing, large language models, graph theory, link analysis, optimization models, complex adaptive systems, or deep-learning neural networks.
  • Experience using programming languages, query languages, data-intelligence platforms, and data-storage technologies, including R, Python, Structured Query Language (SQL), Java, Databricks, Sybase, Oracle, or open-source databases, to retrieve, process, query, analyze, and integrate data during data science projects.
  • Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing technical deliverables for validity and reliability; and communicating analytical findings, model results, limitations, conclusions, and recommendations to technical and nontechnical stakeholders through written products, presentations, graphs, tables, charts, or business-intelligence products.


AND
You must also meet the following requirement(s):

  • TIME AFTER COMPETITIVE APPOINTMENT (TACA): By the closing date (or if this is an open continuous announcement, by the cut-off date) specified in this job announcement, current civilian employees must have completed at least 90 days of federal civilian service since their latest non-temporary appointment from a competitive referral certificate, known as time after competitive appointment. For this requirement, a competitive appointment is one where you applied to and were appointed from an announcement open to "All US Citizens"
  • TIME IN GRADE (TIG): For positions above the GS-05,applicants must meet applicable time-in-grade requirements to be considered eligible. One year (52 weeks) at the next lower grade level is required to meet the time-in-grade requirements for the grade you are applying for. For positions at the GS-05, you cannot advance to the GS-05 if you have held a GS-02 in the past 52 weeks. There is no TIG restriction for GS-02, 03 or 04 positions.


For more information on qualifications please refer to OPM's Qualifications Standards.

Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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