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Junior R Shiny Developer Jobs (NOW HIRING)

CEDENT

R Programmer

Washington, DC · Remote

Develop data science tool with R Shiny as the web framework and deploy the artifacts into RStudio ... & DevOps functions. * 3+ years solid development experience in R, R packages, RStudio, RStudio ...

CEDENT

R Programmer (Washington, DC)

Washington, DC · Remote

Develop data science tool with R Shiny as the web framework and deploy the artifacts into RStudio ... & DevOps functions. 3+ years solid development experience in R, R packages, RStudio, RStudio ...

Cedent

R Programmer (Washington, DC)

Washington, DC · On-site

Develop data science tool with R Shiny as the web framework and deploy the artifacts into RStudio ... & DevOps functions. * 3+ years solid development experience in R, R packages, RStudio, RStudio ...

AITHERAS, LLC

Junior Data Scientist

Arlington, VA · On-site

$100K - $120K/yr

Junior Data Scientist / Performance Data Analyst I Location: Washington, DC / Hybrid / Government ... R experience using tidyverse, tidymodels, ggplot2, Shiny, or equivalent packages. * SQL experience ...

AITHERAS, LLC

Junior Data Scientist

Arlington, VA · On-site

$100K - $120K/yr

Junior Data Scientist / Performance Data Analyst I Location: Washington, DC / Hybrid / Government ... R experience using tidyverse, tidymodels, ggplot2, Shiny, or equivalent packages. * SQL experience ...

Contemporaries

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Data Scientist

Durham, NC · Remote

$51 - $58/hr

... R programming language * Experience working with large-scale geospatial or environmental datasets * Experience developing dashboards or interactive visualizations using R Shiny * Experience with ...

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How much do junior r shiny developer jobs pay per year?

As of May 30, 2026, the average yearly pay for junior r shiny developer in the United States is $88,976.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $87,000.00 per year, depending on experience, location, and employer.

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 are Junior R Shiny Developers?

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 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.

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Junior R Shiny Developer jobs near you

R Shiny Developer

Texas State Library and Archives Commision

Remote

Full-time

Posted 2 days ago

Job description

Required Skills : Technical Skills : R Shiny ,R Studio
Domain Skills : 5. Nice to have skills : Technical Skills : PL/SQL ,3NF data modeling Domain Skills : Research and Development
Technology : Analytics
Roles & Responsibilities : As a Technical Lead, you will be responsible for leading a team of developers, designing and implementing technical solutions, conducting code reviews, and providing technical guidance and mentorship. You will collaborate with cross-functional teams to ensure the successful delivery of projects and contribute to the overall technical strategy of the organization.
Key Responsibilities:
1. R Shiny Application Development: Create and maintain interactive web applications using R Shiny, allowing end-users to visualize and interact with data in an intuitive manner.
2. Data Visualization: Collaborate with data scientists, analysts, and stakeholders to design visually compelling and user-friendly dashboards, charts, and reports.
3. Front-End Development: Implement responsive and user-friendly user interfaces using HTML, CSS, and JavaScript to enhance the user experience.
4. Data Integration: Integrate data from various sources, including databases, APIs, and flat files, ensuring data accuracy and reliability.
5. Performance Optimization: Identify and resolve performance bottlenecks in Shiny applications to ensure smooth and efficient user interactions.
6. Quality Assurance: Conduct thorough testing and debugging of Shiny applications to ensure functionality, reliability, and security.
7. Documentation: Maintain comprehensive documentation for code, applications, and processes to facilitate knowledge sharing and team collaboration.
8. Collaboration: Collaborate with cross-functional teams, including data scientists, analysts, and project managers, to understand project requirements and deliver solutions that meet business objectives.
9. Stay Current: Stay updated on the latest trends and best practices in R Shiny development and data visualization to continuously improve our applications.

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