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Full Time R Shiny Developer Jobs (NOW HIRING)

Goldbelt Apex

Bioinformatician

Atlanta, GA · On-site

Develop bioinformatics pipelines using parallel programming capabilities through workflow tools ... Work with and/or develop dashboarding tools, including Power BI, Tableau, and R Shiny, to manage ...

Goldbelt, Inc.

Bioinformatician

Atlanta, GA · On-site

Develop bioinformatics pipelines using parallel programming capabilities through workflow tools ... Work with and/or develop dashboarding tools, including Power BI, Tableau, and R Shiny, to manage ...

MD Anderson

Postdoctoral Fellow - Biostatistics

Houston, TX · On-site +1

$64K - $76K/yr

... programming and computational skills; gain interest in statistical methodology research; and ... R, R Shiny, and React. ELIGIBILITY REQUIREMENTS We seek a highly motivated individual with a Ph.D ...

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How much do full time r shiny developer jobs pay per hour?

As of May 31, 2026, the average hourly pay for full time r shiny developer in the United States is $49.33, according to ZipRecruiter salary data. Most workers in this role earn between $26.44 and $67.31 per hour, depending on experience, location, and employer.

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

AspectFull Time R Shiny DeveloperData Analyst
Primary focusDeveloping interactive web applications using R ShinyAnalyzing data to generate reports and insights
Skills requiredR programming, Shiny framework, web development basicsData manipulation, statistical analysis, visualization
Work environmentSoftware development teams, tech companies, consulting firmsBusiness units, research departments, analytics teams
Common certificationsR programming certifications, data science certificationsData analysis or business intelligence certifications

While both roles require proficiency in R, Full Time R Shiny Developers focus on building interactive applications, whereas Data Analysts concentrate on interpreting data and creating reports. The developer role emphasizes coding and web app deployment, while the analyst role centers on data insights and visualization.

More about Full Time R Shiny Developer jobs
What are the most commonly searched types of R Shiny Developer jobs? The most popular types of R Shiny Developer jobs are:
What job categories do people searching Full Time R Shiny Developer jobs look for? The top searched job categories for Full Time R Shiny Developer jobs are:
Full Time R Shiny Developer jobs near you
Infographic showing various Full Time R Shiny Developer job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 45% In-person, and 55% Remote job distribution, with an average salary of $102,607 per year, or $49.3 per hour.

R Shiny Developer

Texas State Library and Archives Commision

Remote

Full-time

Posted 3 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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