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Data Analyst R Jobs in Oklahoma (NOW HIRING)

Proficiency in Python, R, SQL, or similar data analysis languages. * Experience using software libraries such as pandas, NumPy, scikit-learn, TensorFlow, PyTorch, or similar tools. * Experience ...

Proficiency in Python, R, SQL, or similar data analysis languages. * Experience using software libraries such as pandas, NumPy, scikit-learn, TensorFlow, PyTorch, or similar tools. * Experience ...

Help define scalable data models and structures to support analytics and AI use cases Tooling & Infrastructure * Build models and workflows using: * Python (preferred) or R * SQL / BigQuery (GCP ...

Proficiency in Python, R, SQL, or similar data analysis languages. * Experience using software libraries such as pandas, NumPy, scikit-learn, TensorFlow, PyTorch, or similar tools. * Experience ...

Showing results 21-40

Data Analyst R information

See Oklahoma salary details

$31.4K

$76.3K

$125.6K

How much do data analyst r jobs pay per year?

As of Jul 25, 2026, the average yearly pay for data analyst r in Oklahoma is $76,304.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,700.00 and $89,600.00 per year, depending on experience, location, and employer.

What is the highest paying data analyst job?

Senior data analyst roles, especially those involving advanced skills in machine learning, big data tools, and business intelligence platforms, tend to offer the highest salaries for data analysts. Positions in finance, technology, and consulting industries often provide higher compensation, with some senior or specialized roles earning over $100,000 annually depending on experience and location.

What is a Data Analyst R job?

A Data Analyst R job involves analyzing and interpreting data using the R programming language. Professionals in this role collect, clean, and process data, then apply statistical techniques and visualizations to extract insights. They work with databases, create reports, and support decision-making in business, healthcare, finance, or other industries. Proficiency in R, SQL, and data visualization tools is essential.

Can you use R for data analysis?

Data Analysts often use R for data analysis because it offers extensive statistical and graphical capabilities, along with a wide range of packages for data manipulation and visualization. Proficiency in R can enhance a data analyst's ability to interpret complex datasets and generate insights efficiently.

What are the key skills and qualifications needed to thrive in the Data Analyst R position, and why are they important?

To excel as a Data Analyst R, candidates require strong analytical abilities, proficiency in statistical modeling, and a solid background in mathematics or related fields, often supported by a relevant degree. Expertise in the R programming language, knowledge of data visualization libraries, and experience with database querying (such as SQL) are commonly expected; certifications in data analysis or R programming can be advantageous. Attention to detail, critical thinking, and effective communication skills help data analysts translate complex data insights into actionable business recommendations. These competencies enable Data Analyst R professionals to accurately interpret data, efficiently support business decisions, and foster collaboration across departments.

Is R important for data analysts?

R is an important tool for data analysts as it provides extensive statistical and data visualization capabilities. Proficiency in R can enhance data analysis, modeling, and reporting skills, making it a valuable skill in many data-focused roles.

Do data analysts still use R?

Data analysts still use R as it remains a popular programming language for statistical analysis, data visualization, and data manipulation. Many organizations value R for its extensive package ecosystem and open-source nature, often alongside tools like Python and SQL. Proficiency in R can enhance a data analyst's ability to perform complex analyses and communicate insights effectively.

What does a typical day look like for a Data Analyst R, and how do they work with other teams?

A Data Analyst R typically spends their day extracting, cleaning, and analyzing large datasets using R, generating reports, and building data visualizations to communicate findings. Collaboration is a key aspect, as analysts often work closely with business stakeholders, IT teams, and fellow analysts or data scientists to define project objectives and interpret results. Regular meetings, presentation of findings, and participation in problem-solving discussions are common parts of the workflow. This collaborative, dynamic environment helps ensure that data-driven insights effectively support organizational goals and decision-making processes.

Infographic showing various Data Analyst R job openings in Oklahoma as of July 2026, with employment types broken down into 100% Full Time. Highlights an 91% In-person, and 9% Hybrid job distribution, with an average salary of $76,304 per year, or $36.7 per hour.
Data Scientist-Direct Hire

Data Scientist-Direct Hire

US Department of the Treasury

Lawton, OK • On-site

$74K/yr

Other

Posted 19 days ago


U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

244th of 705 rated public administrative organizations


Job description

WHAT IS DATA AND ANALYTICS (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)?
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 the following area(s):
    • DAO - DATA AND ANALYTICS
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
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 cut-off dates as shown in announcement under the 'How to Apply' section.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS All GRADES: EDUCATION:
You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education with at least 30 semester hours related to Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
EDUCATION/SPECIALIZED EXPERIENCE FOR GS-11: In addition to meeting basic requirements, to be eligible for this position, you must have at least one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal Service. Specialized experience for this position includes: Applying descriptive or inferential statistical methods to analyze data, identify trends or patterns, evaluate results, and develop findings, reports, or recommendations; Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, analyze, or prepare data for analysis; Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform); Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings; and Creating reports, dashboards, visualizations, written summaries, or presentations to communicate statistical or technical findings to technical or non-technical audiences.
OR
EDUCATION: You may substitute education for specialized experience as follows: A Ph.D. or equivalent doctoral degree as described in the basic requirements in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
Three (3) full academic years of progressively higher-level graduate education leading to a PH.D or equivalent doctoral degree in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education.
SPECIALIZED EXPERIENCE GRADE 12: In addition to the basic requirements above, to be eligible for this position at the GS-12 level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Planning and carrying out data analysis assignments by applying descriptive or inferential statistical methods to analyze data from multiple sources, validate results, identify trends or patterns, and develop findings, reports, or recommendations.
  • Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, validate, analyze, visualize, or document structured or unstructured data for data science projects.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, prescriptive analysis, or exploratory data analysis, to evaluate data, models, programs, or operations and make projections or recommendations.
  • Creating and presenting reports, dashboards, visualizations, written summaries, or presentations that explain statistical or technical methods, findings, limitations, or recommendations to managers, stakeholders, customers, or project teams.

SPECIALIZED EXPERIENCE GRADE 13: In addition to the basic requirements above, to be eligible for this position at the GS-13 level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Independently planning and carrying out data science or statistical analysis projects by defining analytic questions, selecting data sources or methods, analyzing structured or unstructured data, validating results, and developing findings or recommendations.
  • Developing or applying statistical, machine learning, operations research, or other data science methods to evaluate programs, operations, compliance, or organizational performance, for example forecasting, predictive or prescriptive modeling, optimization, natural language processing or text analytics, graph or link analysis, or exploratory data analysis.
  • Using programming, query, scripting, or analytic tools, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to prepare, transform, document, analyze, and visualize data for data science projects.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Documenting analytic approaches, assumptions, limitations, validation results, success measures, or key performance indicators, and presenting technical findings or recommendations to managers, stakeholders, customers, or cross-functional teams.

AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

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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