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Full Time Data Analyst R Programming Jobs (NOW HIRING)

Centurion Health

Data Analyst (76789)

Jefferson City, MO · On-site

We are currently seeking a full-time Data Analyst to join our Regional office in Jefferson City, MO ... R, and/or Python experience * 3 + years BI Software experience (Tableau, Power BI, Qlik, etc.) We ...

Centurion

Data Analyst (76789)

Jefferson City, MO · On-site

We are currently seeking a full-time Data Analyst to join our Regional office in Jefferson City, MO ... R, and/or Python experience * 3 + years BI Software experience (Tableau, Power BI, Qlik, etc.) We ...

BrightStar Credit Union

Jr. Data Analyst

Hollywood, FL · On-site

$62K - $75K/yr

Experience with programming languages such as Python or R for data analysis. * Familiarity with statistical methods and predictive modeling techniques. * Previous internship or work experience in a ...

Citizens

Data Analyst

Coralville, IA · On-site

Utilizing R programming to collect, process, and analyze data using visual and statistical analysis techniques; Utilizing Rattle to conduct predictive modeling; Utilizing Tableau to create ...

Altair Data Resources, Inc

Data Analyst

Brentwood, TN · On-site

... Python, Power BI, R and SQL. Data Analyst Job Duties Data analyst responsibilities include ... SQL etc.), programming (Python, JavaScript, or ETL frameworks) * Knowledge of statistics and ...

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How much do full time data analyst r programming jobs pay per year?

As of Jun 18, 2026, the average yearly pay for full time data analyst r programming in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What is the difference between Full Time Data Analyst R Programming vs Data Scientist?

AspectFull Time Data Analyst R ProgrammingData Scientist
Required SkillsData analysis, R programming, SQL, ExcelData analysis, R/Python, machine learning, statistics
Work EnvironmentBusiness, finance, healthcare, corporate settingsResearch, tech companies, startups, academia
CertificationsData analysis, R certifications, SQL certificationsData science, machine learning, Python/R certifications

Full Time Data Analysts R Programming focus on analyzing data using R, often within business environments, while Data Scientists employ advanced statistical and machine learning techniques to extract insights, often working on complex models and algorithms. Both roles require strong analytical skills, but Data Scientists typically have a broader skill set including programming languages like Python and expertise in machine learning.

More about Full Time Data Analyst R Programming jobs
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What are the most commonly searched types of Data Analyst R Programming jobs? The most popular types of Data Analyst R Programming jobs are:
What states have the most Full Time Data Analyst R Programming jobs? States with the most job openings for Full Time Data Analyst R Programming jobs include:
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Full Time Data Analyst R Programming jobs near you
Infographic showing various Full Time Data Analyst R Programming job openings in the United States as of June 2026, with employment types broken down into 5% As Needed, 67% Full Time, 5% Part Time, 5% Temporary, and 18% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Data Analyst

WFN Team Indus US Test Client 2

Manhattan, NY • On-site

Full-time

Posted 18 days ago

Job description

About the Role:

As a Data Analyst at our Agriculture company, your main objective will be to analyze and interpret complex data sets to provide valuable insights and recommendations. You will be responsible for collecting, cleaning, and organizing large volumes of data from various sources. By utilizing your expertise in data cleaning, pivot tables, R programming language, SAS, and data visualization tools such as Power BI and Tableau, you will create visually appealing and informative reports and dashboards. Your analysis will play a crucial role in identifying trends, patterns, and opportunities for improvement in our agricultural operations.

Minimum Qualifications:

  • Bachelor's degree in a relevant field such as Data Science, Statistics, or Mathematics.
  • Proven experience in data analysis and visualization.
  • Proficiency in data cleaning techniques and working with pivot tables.
  • Strong programming skills in R and familiarity with SAS.
  • Excellent problem-solving and critical thinking abilities.

Preferred Qualifications:

  • Master's degree in Data Science or a related field.
  • Experience in the agriculture industry or a similar field.
  • Knowledge of data extraction techniques and tools.
  • Familiarity with machine learning algorithms and predictive modeling.
  • Certifications in data analysis or related areas.

Responsibilities:

  • Collect, clean, and organize large volumes of data from multiple sources.
  • Analyze and interpret complex data sets to identify trends, patterns, and insights.
  • Create visually appealing and informative reports and dashboards using data visualization tools such as Power BI and Tableau.
  • Collaborate with cross-functional teams to understand business requirements and provide data-driven recommendations.
  • Stay up-to-date with the latest industry trends and advancements in data analysis techniques.

Skills:

In this role, your expertise in data cleaning, pivot tables, R programming language, SAS, and data visualization tools such as Power BI and Tableau will be essential. You will use data cleaning techniques to ensure the accuracy and integrity of the collected data. Pivot tables will help you summarize and analyze large datasets efficiently. R programming language and SAS will be used for statistical analysis and modeling. Data visualization tools like Power BI and Tableau will enable you to create visually appealing reports and dashboards to communicate insights effectively. Your skills will be crucial in providing data-driven recommendations and identifying opportunities for improvement in our agricultural operations.