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Entry Level Data Analyst R Programming Jobs in Greenville, SC

Instrata

Data Center Field Engineer

Spartanburg, SC · On-site

... Data Center Field Engineer / Project Engineer to support hyperscale data center construction ... entry-level candidates). * Working knowledge of Division 27/28 conveyance systems preferred ...

Purpose Financial

Marketing Analyst

Greenville, SC · On-site

This includes statistical analysis of various data sources to support marketing projects, tests ... Partner with data quality engineers and data governance team to implement appropriate solutions as ...

Michelin

Industrial Engineer

Spartanburg, SC · On-site

$68K - $92K/yr

... Entry level training is provided by Michelin and will include formal classes and on-the-job ... Microsoft Office Excel data analysis proficiency. Microsoft Power Bi a plus. #LI-HIRINGMICHELIN #LI ...

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Entry Level Data Analyst R Programming information

See Greenville, SC salary details

$12

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$58

How much do entry level data analyst r programming jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for entry level data analyst r programming in Greenville, SC is $30.96, according to ZipRecruiter salary data. Most workers in this role earn between $19.90 and $34.57 per hour, depending on experience, location, and employer.

What is an entry level data analyst r programming?

An Entry Level Data Analyst (R Programming) is a professional who uses the R programming language to collect, process, and analyze data to help organizations make informed decisions. They typically work with large datasets, create visualizations, and generate reports under the guidance of more experienced analysts. Entry-level data analysts are often responsible for basic data cleaning, statistical analysis, and supporting team projects while they develop their skills in R and data analysis techniques.

What skills and qualifications are needed to thrive as an entry level data analyst r programming?

To thrive as an Entry Level Data Analyst specializing in R Programming, you need a solid grounding in statistics, data cleaning, and analytical methods, typically supported by a relevant degree such as statistics, mathematics, or computer science. Proficiency in R programming, familiarity with data visualization tools (e.g., ggplot2), and experience with spreadsheet software or SQL are commonly required. Strong attention to detail, problem-solving abilities, and clear communication skills set outstanding candidates apart in this role. These skills are crucial to accurately interpret data, deliver actionable insights, and effectively collaborate with teams to support data-driven decision-making.

What are some typical challenges entry level data analysts face when working with R programming in a team setting?

Entry-level data analysts using R often encounter challenges such as adapting to existing codebases, understanding team-specific data workflows, and ensuring code reproducibility and documentation for collaborative projects. New analysts may also need to quickly learn version control practices (like using Git) and follow standardized procedures for data cleaning and reporting. Regular communication with senior analysts and participation in code reviews are essential to build both technical proficiency and teamwork skills.

What is the difference between Entry Level Data Analyst R Programming vs Data Scientist?

AspectEntry Level Data Analyst R ProgrammingData Scientist
Required SkillsBasic R programming, data cleaning, visualization, ExcelAdvanced R, Python, machine learning, statistical modeling
Work EnvironmentBusiness, finance, marketing teamsResearch, tech, healthcare, diverse industries
CertificationsData analysis, R programming coursesData science, machine learning certifications

Entry Level Data Analyst R Programming roles focus on data cleaning, visualization, and basic analysis using R, often within business environments. Data Scientists require advanced statistical and programming skills, including machine learning, and work on complex predictive models across various industries. While both roles involve data handling, Data Scientists typically have a broader skill set and handle more complex projects.

What are the most commonly searched types of Data Analyst R Programming jobs in Greenville, SC?

The most popular types of Data Analyst R Programming jobs in Greenville, SC are:

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For Entry Level Data Analyst R Programming jobs in Greenville, SC, the most frequently searched job titles are:

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Entry Level Data Analyst R Programming jobs near you
Infographic showing various Entry Level Data Analyst R Programming job openings in Greenville, SC as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $64,398 per year, or $31 per hour.

Data Scientist (Statistician) - Direct Hire

US Department of the Treasury

Greenville, SC • On-site

$125K/yr

Full-time

Posted 5 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

311th of 854 rated public administrative organizations

Job description

WHAT IS LARGE BUSINESS AND INTERNATIONALDIVISION?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position is to be filled in the following area(s):
    • LBI - ADCCI - Assistant Deputy Commissioner Compliance Integration.


REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILS

Qualifications: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.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
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 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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