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From Home R Shiny Developer Jobs (NOW HIRING)

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 ...

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 ...

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 ...

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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 ...

... from multiple users in a database * Using PL/SQL to build and schedule stored procedures that ... Experience building R Shiny and Tableau dashboards * Experience using Oracle and PostgreSQL ...

... from multiple users in a database * Using PL/SQL to build and schedule stored procedures that ... Experience building R Shiny and Tableau dashboards * Experience using Oracle and PostgreSQL ...

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From Home R Shiny Developer information

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$13

$49

$88

How much do from home r shiny developer jobs pay per hour?

As of May 31, 2026, the average hourly pay for from home 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 From Home R Shiny Developer vs From Home Data Analyst?

AspectFrom Home R Shiny DeveloperFrom Home Data Analyst
Required SkillsProficiency in R, Shiny, data visualizationData analysis, Excel, SQL, visualization tools
Work EnvironmentRemote, project-basedRemote, reporting-focused
Industry UsageTech, healthcare, financeMarketing, finance, consulting

While both roles often work remotely and require data skills, From Home R Shiny Developers focus on building interactive web applications using R, whereas From Home Data Analysts analyze data sets to generate insights. The developer role emphasizes coding and app deployment, while the analyst role centers on data interpretation and reporting.

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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.