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Junior R Statistical Programmer Jobs in South Carolina

Senior Data Scientist

Hanahan, SC · On-site

$48.56 - $77.69/hr

Provide technical guidance and mentorship to junior analysts and data scientists * Document ... Master's degree in Data Science, Computer Science, Mathematics, Statistics, Engineering ...

Senior Data Scientist

Hanahan, SC · On-site

$48.56 - $77.69/hr

Provide technical guidance and mentorship to junior analysts and data scientists * Document ... Master's degree in Data Science, Computer Science, Mathematics, Statistics, Engineering ...

Senior Data Scientist

Hanahan, SC · On-site

$48.56 - $77.69/hr

Provide technical guidance and mentorship to junior analysts and data scientists * Document ... Master's degree in Data Science, Computer Science, Mathematics, Statistics, Engineering ...

Senior Data Scientist

Hanahan, SC · On-site

$48.56 - $77.69/hr

Provide technical guidance and mentorship to junior analysts and data scientists * Document ... Master's degree in Data Science, Computer Science, Mathematics, Statistics, Engineering ...

Showing results 21-40

Junior R Statistical Programmer information

What is a junior R statistical programmer?

Junior R Statistical Programmers are entry-level professionals who use the R programming language to analyze data, create statistical models, and generate reports, often for research, healthcare, or business purposes. They typically assist senior statisticians or data scientists by cleaning data, writing scripts, and performing basic statistical analyses. Their role helps organizations turn raw data into actionable insights, and they often work as part of a larger analytics or research team.

What are the key skills and qualifications needed to thrive as a junior R statistical programmer?

To thrive as a Junior R Statistical Programmer, you need a solid understanding of statistical concepts, programming proficiency in R, and a bachelor's degree in statistics, mathematics, computer science, or a related field. Familiarity with data management tools like SQL, version control systems such as Git, and statistical analysis packages in R is typically expected. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate with team members and clearly present analytical findings. These competencies ensure accurate data analysis, reproducible results, and successful teamwork within research or business environments.

What are typical challenges a junior R statistical programmer might face when transitioning from academic projects to industry settings?

Junior R Statistical Programmers often find the shift from academic to industry work entails adapting to stricter timelines, code standardization, and collaborative workflows. In industry, you may need to follow specific documentation practices, utilize version control systems like Git, and adapt your code for scalability and reproducibility. Additionally, you’ll frequently collaborate with statisticians, data managers, and project leads, which requires strong communication skills and the ability to incorporate feedback from multiple stakeholders.

What is the difference between Junior R Statistical Programmer vs Data Analyst?

AspectJunior R Statistical ProgrammerData Analyst
Required SkillsProficiency in R, basic statistical knowledge, programming skillsData manipulation, visualization, statistical analysis, often using R or Excel
Work EnvironmentPharmaceutical or clinical research settings, working on data processing and reportingBusiness, marketing, or healthcare sectors analyzing large datasets for insights
CertificationsOften requires a degree in statistics, biostatistics, or related field; certifications like SAS or R preferred

While both roles involve data analysis and R programming, Junior R Statistical Programmers focus more on clinical or research data processing within regulated environments, whereas Data Analysts work across various industries analyzing business data. The roles share skills but differ in context and application.

What are the most commonly searched types of R Statistical Programmer jobs in South Carolina?

The most popular types of R Statistical Programmer jobs in South Carolina are:

What are popular job titles related to Junior R Statistical Programmer jobs in South Carolina?

For Junior R Statistical Programmer jobs in South Carolina, the most frequently searched job titles are:

What job categories do people searching Junior R Statistical Programmer jobs in South Carolina look for?

The top searched job categories for Junior R Statistical Programmer jobs in South Carolina are:

What cities in South Carolina are hiring for Junior R Statistical Programmer jobs?

Cities in South Carolina with the most Junior R Statistical Programmer job openings:

Infographic showing various Junior R Statistical Programmer job openings in South Carolina as of August 2026, with employment types broken down into 2% Internship, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

Data Scientist (Statistician) - Direct Hire

Florence, SC • On-site

US Department of the Treasury
Public Administration • 10K+ employees

$125K/yr

Full-time

Posted 13 days ago


Key responsibilities

  • Identify and assess the validity and reliability of relevant data sources and retrieve structured and unstructured data for data science projects.

  • Clean, transform, combine, and integrate data from multiple sources to prepare it for analysis.

  • Apply data-mining process models and statistical methods to analyze data, evaluate results, and support program or business decisions.


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 858 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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