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Junior R Shiny Developer Jobs in North Carolina (NOW HIRING)

Associate Epidemiologist

Charlotte, NC · On-site

$53K - $88K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Experience working with large datasets using one or more statistical programming languages such as ... Experience developing dashboards using Power BI, Tableau, R Shiny, or similar platforms.

Quantitative Associate

Durham, NC · On-site

$125K - $140K/yr

  • Medical

  • Dental

  • Retirement

... Engineering, or Mathematics. * A demonstrated passion for investing and a strong desire to learn ... Experience building dashboards and data visualizations using tools like R Shiny, Python Dash ...

Quantitative Associate

Durham, NC

$125K - $140K/yr

  • Medical

  • Dental

  • Retirement

... Engineering, or Mathematics. * A demonstrated passion for investing and a strong desire to learn ... Experience building dashboards and data visualizations using tools like R Shiny, Python Dash ...

Junior Biostatistician

Fort Liberty, NC · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Junior Biostatistician supports data engineering, statistical analysis, and analytics functions ... Foundational programming skills in Python or R for analysis, data manipulation, and ML workflows.

... R Programming, Python, Spark • Statistical & Data Management Packages - Python - Pandas, Numpy ... • Visualization - Tableau, Shiny, ggplot2, dygraphs, matplotlib, seaborn • Big Data ...

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Showing results 1-20

Junior R Shiny Developer information

What is a Junior R Shiny developer?

Junior R Shiny Developers are entry-level professionals who build interactive web applications using the R programming language and the Shiny framework. They typically work under the guidance of senior developers to design, develop, and maintain data-driven dashboards and tools. Their tasks often include writing R code, creating user interfaces, visualizing data, and ensuring applications run smoothly. This role is ideal for individuals with a background in statistics, data analysis, or programming who are looking to gain experience in web development and data science applications.

What are the key skills and qualifications needed to thrive as a Junior R Shiny developer, and why are they important?

To excel as a Junior R Shiny Developer, you need a solid understanding of R programming, data analysis, and basic web development concepts, typically supported by a degree in computer science, statistics, or a related field. Familiarity with the Shiny package, Git version control, and data visualization tools like ggplot2 is commonly required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills for this role. These competencies ensure the delivery of robust, user-friendly data applications that meet client or organizational needs.

What are some common challenges faced by Junior R Shiny developers during project development?

Junior R Shiny Developers often encounter challenges related to translating user requirements into interactive web applications, managing reactivity efficiently, and ensuring application performance with larger datasets. Navigating unfamiliar codebases, debugging reactive expressions, and learning best practices for UI/UX design in Shiny are also typical hurdles. Collaborating closely with data scientists and end users is essential to refine features and ensure the app meets practical needs, so strong communication and a willingness to learn from feedback are key to success in this role.

What is the difference between Junior R Shiny Developer vs Data Analyst?

AspectJunior R Shiny DeveloperData Analyst
Required SkillsProficiency in R, Shiny, basic programmingData manipulation, statistical analysis, visualization
Work EnvironmentDeveloping interactive web apps, codingData interpretation, reporting, dashboards
Industry UsageTech, healthcare, finance for app developmentBusiness, marketing, finance for insights

While both roles involve working with data, a Junior R Shiny Developer primarily focuses on creating interactive web applications using R and Shiny, requiring coding skills. In contrast, a Data Analyst interprets data, generates reports, and provides insights, often using tools like Excel, SQL, or visualization software. The roles overlap in data handling but differ in technical depth and end goals.

What are the most commonly searched types of R Shiny Developer jobs in North Carolina?

The most popular types of R Shiny Developer jobs in North Carolina are:

What job categories do people searching Junior R Shiny Developer jobs in North Carolina look for?

The top searched job categories for Junior R Shiny Developer jobs in North Carolina are:

Infographic showing various Junior R Shiny Developer job openings in North Carolina as of August 2026, with employment types broken down into 79% Full Time, 3% Part Time, and 18% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution.

Junior Data Scientist

Altamira Technologies Corp.

Fort Liberty, NC • On-site

Full-time

Posted 15 days ago


Job description

Altamira Technologies has a long and successful history providing innovative solutions throughout the U.S. National Security community. Headquartered in McLean, Virginia, Altamira serves the defense, intelligence and homeland security communities worldwide by focusing on creating innovative solutions leveraging common standards in architecture, data and security. Altamira believes that our people and the culture of our company differentiate us from other companies.

Position: Junior Data Scientist

Position Location: Fort Bragg, North Carolina

Position Description:
A data scientist will have skills sets of both data analysts and data engineers. Data scientists are responsible for designing, implementing, and maintaining a data pipeline.  In addition, data scientists shall interpret and analyze complex sets of data, as well as plan, execute, and manage ML projects with cloud-native platforms and advanced ML solutions. They understand some of the most challenging processes, technologies, and can leverage a vast array of methodologies in the field, such as data mining, natural language programming, and machine learning.

Data scientists must have a combination of skills that include programming, mathematical modeling, statistics, and domain knowledge. They must combine an advanced math and statistics background with programming, domain knowledge, and communication skills to analyze data, create applied mathematical models, and present results in a form useful to the organization.  They must also be able to understand and manipulate structured and unstructured large data sets, which requires proficiency in distributed SQL programming, relational and non-relational data queries, general programming languages (such as Python and R,) and machine learning techniques.

Experience:

  • Interpret and analyze data using exploratory mathematicand statistical techniques based on the scientific method.
  • Coordinate research and analytic activities utilizing various data points (unstructured and structured) and employ programming to clean, massage, and organize the data
  • Experiment against data points, provide information based on experiment results and provide previously undiscovered solutions to command data challenges.
  • Coordinate with Data Engineers to build Data environments providing data identified by other data professionals
  • Apply and develop scientific methodology, statistics, and algorithms to discover and frame relevant problems, hypotheses, and opportunities.
  • Develop predictive and prescriptive modeling, natural language processing (NLP), Robotic Process Automation (RPA), text mining and processing, clustering, forecasting methods, and other advanced statistical techniques.
  • Design and automate processes to facilitate the manipulation and analysis of data. Manage and integrate data across dissimilar data sets. Analyze large-scale structured and unstructured data.
  • Use frameworks such as Spark and Hadoop to conduct large-scale data processing. Perform statistical modeling and create data visualizations using products like Tableau, Microsoft Power BI and R Shiny.
  • Research, design, and implement algorithms to solve complex problems. Program using R, Python (NumPy, SciPy, Pandas) or similar analytical languages.
  • Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, and Snowflake.
  • Communicate complex concepts and hypothesis to a non-technical audience through digital storytelling.

Education:

  • Bachelor’s degree in a STEM field is required.  Master’s degree is preferred in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or related fields.
  • Bachelor’s degree is acceptable in the above fields if the incumbent has training and verifiable work experience in a related field.
  • Proficient with one or more programming languages (Java, C++, Python, R, etc.).
  • Proficient in Agile Development and Git Operations.
  • Demonstrated experience applying data science methods to real-world data problems.
  • TS/SCI clearance is preferred
  • Minimum SECRET Clearance to start with the willingness and ability to obtain TS/SCI.