R & RShiny Developer

Trigent Software Private Limited

Job Location:

Bengaluru - India

Monthly Salary: Not Disclosed

Posted on: 06-11-2025

Vacancies: 1 Vacancy

Job Summary

Key Responsibilities Design build and deploy advanced RShiny applications on cloud platforms ensuring they are scalable and performant for large-scale clinical data analysis. Collaborate with data scientists biostatisticians and research teams to create sophisticated RShiny applications that drive our clinical data analysis efforts. Utilize tools like Posit Workbench Posit Connect and AWS services to create workflows that support the deployment of R-based analytics applications. Develop and maintain robust data pipelines to pull process and visualize large datasets from data sources (Databricks) within RShiny applications. Work closely with data engineers and architects to ensure the seamless integration of data sources (Databricks) and tools used within the organization. Create and maintain technical documentation to support ongoing development and deployment processes. Required Qualifications Minimum of 5 years of experience in the IT industry with a strong emphasis on data visualization and dashboard development particularly using R. Proven experience in the Life Sciences Biotech or Pharma industry is a must. Bachelors degree in computer science Engineering Information Systems Data Science or a related field is required. A masters degree is preferred. 3 years of hands-on experience with R R packages RStudio and RShiny particularly in the context of clinical data analysis. 2 years of experience in building and maintaining CI/CD tooling (e.g. Gitlab GitHub). Basic knowledge of SQL for querying databases and manipulating data within both relational databases and big data environments. Experience in integrating RShiny applications with various data sources particularly cloud-based data storage solutions like AWS S3 Azure Data Lake or similar platforms. Ability to effectively communicate technical solutions to both engineering teams and business audiences. Additional Qualifications for RShiny Development Advanced Shiny TechniquesProficiency in using shiny modules JS events and custom bindings to extend the functionality of Shiny applications. User-Centric DesignStrong ability to implement visually appealing and user-friendly applications using HTML/CSS. Ability to scale Shiny applications to hundreds of users with experience in performance optimization at various levels (frontend backend infrastructure). Other Key Skills Validation and ComplianceExperience in validating RShiny applications to meet regulatory standards such as FDA EMA and GxP guidelines. This ensures that the applications are reliable secure and compliant with industry regulations. Open Source ContributionsActive participation in the open-source community particularly in developing and maintaining R packages and Shiny applications. This demonstrates a commitment to continuous learning and staying updated with the latest advancements in the field. Performance OptimizationExpertise in optimizing the performance of Shiny applications including frontend backend and infrastructure levels to ensure they can handle large datasets and multiple users efficiently. User Behavior AnalysisAbility to analyze user behavior and interactions with Shiny applications to improve usability and functionality. This involves understanding the diverse needs of users ranging from data scientists to clinicians. Data IntegrationProficiency in integrating Shiny applications with various data sources including cloud-based storage solutions like AWS S3 Azure Data Lake and other platforms. Collaboration and CommunicationStrong collaboration skills to work effectively with cross-functional teams including data scientists biostatisticians and IT professionals. Excellent communication skills to convey technical solutions to both technical and non-technical audiences. Named Job Posting (if Yes - needs to be approved by SCSC)

Key Responsibilities Design build and deploy advanced RShiny applications on cloud platforms ensuring they are scalable and performant for large-scale clinical data analysis. Collaborate with data scientists biostatisticians and research teams to create sophisticated RShiny applications that drive...

Key Responsibilities Design build and deploy advanced RShiny applications on cloud platforms ensuring they are scalable and performant for large-scale clinical data analysis. Collaborate with data scientists biostatisticians and research teams to create sophisticated RShiny applications that drive our clinical data analysis efforts. Utilize tools like Posit Workbench Posit Connect and AWS services to create workflows that support the deployment of R-based analytics applications. Develop and maintain robust data pipelines to pull process and visualize large datasets from data sources (Databricks) within RShiny applications. Work closely with data engineers and architects to ensure the seamless integration of data sources (Databricks) and tools used within the organization. Create and maintain technical documentation to support ongoing development and deployment processes. Required Qualifications Minimum of 5 years of experience in the IT industry with a strong emphasis on data visualization and dashboard development particularly using R. Proven experience in the Life Sciences Biotech or Pharma industry is a must. Bachelors degree in computer science Engineering Information Systems Data Science or a related field is required. A masters degree is preferred. 3 years of hands-on experience with R R packages RStudio and RShiny particularly in the context of clinical data analysis. 2 years of experience in building and maintaining CI/CD tooling (e.g. Gitlab GitHub). Basic knowledge of SQL for querying databases and manipulating data within both relational databases and big data environments. Experience in integrating RShiny applications with various data sources particularly cloud-based data storage solutions like AWS S3 Azure Data Lake or similar platforms. Ability to effectively communicate technical solutions to both engineering teams and business audiences. Additional Qualifications for RShiny Development Advanced Shiny TechniquesProficiency in using shiny modules JS events and custom bindings to extend the functionality of Shiny applications. User-Centric DesignStrong ability to implement visually appealing and user-friendly applications using HTML/CSS. Ability to scale Shiny applications to hundreds of users with experience in performance optimization at various levels (frontend backend infrastructure). Other Key Skills Validation and ComplianceExperience in validating RShiny applications to meet regulatory standards such as FDA EMA and GxP guidelines. This ensures that the applications are reliable secure and compliant with industry regulations. Open Source ContributionsActive participation in the open-source community particularly in developing and maintaining R packages and Shiny applications. This demonstrates a commitment to continuous learning and staying updated with the latest advancements in the field. Performance OptimizationExpertise in optimizing the performance of Shiny applications including frontend backend and infrastructure levels to ensure they can handle large datasets and multiple users efficiently. User Behavior AnalysisAbility to analyze user behavior and interactions with Shiny applications to improve usability and functionality. This involves understanding the diverse needs of users ranging from data scientists to clinicians. Data IntegrationProficiency in integrating Shiny applications with various data sources including cloud-based storage solutions like AWS S3 Azure Data Lake and other platforms. Collaboration and CommunicationStrong collaboration skills to work effectively with cross-functional teams including data scientists biostatisticians and IT professionals. Excellent communication skills to convey technical solutions to both technical and non-technical audiences. Named Job Posting (if Yes - needs to be approved by SCSC)