Senior R Shiny Developer

🗓️ Posted 2026-09-17 Ukraine; United Kingdom Hybrid ICT

Company shared salary

NA

Market rate

6,000 GBP–9,000 GBP/mo (72,000 GBP–108,000 GBP/yr)

Based on similar roles (title + domain + location).

About the Company

Veramed is seeking an experienced R Shiny App Developer to join our growing Functional Service Provider (FSP) team, supporting a leading global pharmaceutical organisation. This is an exciting opportunity for an individual who enjoys working at the intersection of statistical methodology, software development, and data analytics. You'll play a key role in developing innovative tools and applications that enable statisticians and programmers to work more efficiently, while supporting advanced analytical methodologies within a collaborative, science-driven environment. Join a people-focused CRO with an industry-leading employee retention rate Work within a collaborative team that values innovation, quality, and continuous learning Contribute to the development of tools that directly support statistical and programming teams Gain exposure to advanced analytical methodologies and real-world healthcare data challenges Work with modern development practices and technologies, including Azure DevOps, CI/CD pipelines, and version-controlled development Be part of a growing international organisation delivering high-quality solutions to leading pharmaceutical clients

About the Role

As an R Shiny App Developer, you will be responsible for designing, developing, and maintaining software tools that bridge statistical methodology and practical application. You'll work closely with statisticians, programmers and cross-functional teams to build reliable, scalable solutions that support data analysis, reporting and decision-making.

Responsibilities

  • Develop and maintain R packages used by statistical and TFL programming teams
  • Build and enhance R Shiny applications that support analytical workflows
  • Contribute to indirect treatment comparison methodologies, including MAIC and Network Meta-Analysis (NMA)
  • Work with both synthetic individual patient data (IPD) and aggregated datasets
  • Develop tools that support datasets, analyses, tables, figures and listings
  • Utilise Azure DevOps for repository management, pipeline automation and agile delivery
  • Collaborate with statisticians and technical stakeholders to translate analytical requirements into user-focused software solutions
  • Unit testing
  • Code reviews
  • Git version control
  • Continuous Integration / Continuous Deployment (CI/CD)
  • R programming and package development
  • R Shiny application development
  • Statistical programming within a regulated or scientific environment
  • Software engineering principles and best practices
  • Git version control and collaborative development
  • CI/CD pipelines and automated testing
  • Azure DevOps or similar development platforms