R Shiny Developer/ Data Scientist (Remote)

Contact: Terra Parsons - 
No 3rd party candidates

This is a hands-on development role for a strong R/Shiny developer who understands clinical trial data and can work directly with clinical study and Biometrics stakeholders to understand their needs and translate them into practical, user-friendly applications, dashboards, and visualizations.

The ideal candidate is a strong R/Shiny developer who understands clinical trial data and can work directly with stakeholders to understand their needs and translate them into practical, user-friendly applications and visualizations.

The primary focus of this role is hands-on development and delivery of Shiny applications and dashboards, rather than building broader technical infrastructure or platforms.

Primary Responsibilities

• Design, develop, and maintain interactive R Shiny applications and dashboards supporting clinical studies and Biometrics teams.
• Work directly with stakeholders to gather requirements and translate business and clinical needs into practical Shiny applications.
• Work with clinical trial data to create tools that improve data access, review, visualization, and decision-making.
• Partner closely with Biostatistics, Statistical Programming, Data Management, and other clinical and technical stakeholders.
• Build applications that allow users to effectively explore, visualize, and interact with clinical study data.
• Enhance and maintain existing Shiny applications as study and stakeholder requirements evolve.
• Develop reusable Shiny components and approaches where appropriate.
• Troubleshoot application, data, and visualization issues and implement practical solutions.
• Participate in application testing, validation, and quality review.
• Communicate effectively with both technical and non-technical stakeholders throughout the development process.

Required Qualifications

• Bachelor's or Master's degree in Data Science, Statistics, Biostatistics, Computer Science, or a related quantitative field.
• Strong hands-on R programming and R Shiny development experience.
• Demonstrated experience personally building Shiny applications, dashboards, and interactive data visualizations.
• Experience developing reusable Shiny modules or components.
• Experience working with clinical trial data within pharmaceutical, biotechnology, CRO, or a related clinical research environment.
• Experience working directly with stakeholders to understand requirements, incorporate feedback, and deliver functional applications.
• Strong understanding of data manipulation and visualization (static and dynamic) in R.
• Experience working with databases or other clinical data sources.
• Familiarity with Git/GitHub and collaborative development practices.
• Strong communication skills and ability to work effectively across technical and clinical functions.
• Ability to work independently and take ownership of Shiny development from requirements through delivery.
• Comfortable working in a fast-moving organization with evolving priorities.

Preferred Experience

• Experience developing Shiny applications specifically for clinical data review, study analytics, or Biometrics teams.
• Experience working alongside Biostatistics, Statistical Programming, and Clinical Data Management.
• Experience with SAS and/or Python is beneficial but not required as a primary skill set.

The successful candidate will be:

• A hands-on Shiny developer. Has meaningful experience personally building applications and dashboards rather than simply supporting or overseeing development.
• Clinical-data savvy. Understands clinical trial data and can apply that knowledge when developing applications and visualizations.
• Stakeholder-oriented. Can gather requirements, ask the right questions, incorporate feedback, and translate stakeholder needs into effective applications.
• Delivery-focused. Enjoys building and delivering useful apps and dashboards and is comfortable spending the majority of their time doing hands-on development.
• Practical. Focused on building effective, usable solutions without overengineering.
• Independent and collaborative. Can own development work while partnering closely with clinical and Biometrics stakeholders.