R Developer with Life Science Background

Role overview

This opportunity is for an R developer based in Ireland, working with a partner company that handles the application process and all follow-up steps. The position combines software engineering, data science, and life sciences to create advanced R-based tools that support research in drug discovery, clinical studies, and biomedical analytics.

You will collaborate with scientists, bioinformaticians, and data engineers to turn complex biological information into interactive, production-ready applications that help inform scientific and clinical decisions. The work environment is collaborative, research-led, and grounded in strong engineering standards, with a strong emphasis on bioinformatics and biostatistics. The role includes end-to-end ownership of data-driven applications and is well suited to someone who enjoys coding while contributing to progress in life sciences.

Accountabilities

• Build, enhance, and support robust R and Shiny applications that enable biological and clinical data analysis.
• Handle complex life science data by processing, analyzing, and visualizing it with attention to accuracy, reproducibility, and ease of use.
• Create and maintain reusable R packages and data-processing building blocks that can scale across analytics products.
• Work closely with scientists, bioinformaticians, and other partners to understand needs and convert them into technical solutions.
• Develop interactive visualization tools that improve research workflows and clinical decision support.
• Use Git and other version control practices to support teamwork and maintain code quality.
• Participate in system design discussions, backlog grooming, and ongoing improvements to development processes.
• Assist with deployment and upkeep of production-level data applications in cloud or distributed setups.

Requirements

• Strong command of R, with practical experience delivering software in production settings.
• Hands-on exposure to biological, clinical, or other life science datasets, including analysis, processing, and visualization.
• Experience developing web applications with R Shiny or JavaScript.
• Ability to create, maintain, and document R packages.
• Good working knowledge of Git and collaborative development methods.
• Master’s degree in Bioinformatics, Data Science, Computer Science, Biostatistics, Mathematics, or a closely related area, or equivalent practical experience.
• Useful knowledge of life science domains such as molecular biology, genomics, or clinical research.
• Capability to convert complex scientific needs into solutions that can be scaled technically.
• Clear communication and strong teamwork skills, especially with scientific stakeholders.
• Experience with reproducible workflows, databases, or cloud environments is advantageous.

Benefits

• Fully remote position with flexible hours designed to support focused work and a healthy work-life balance.
• Competitive pay aligned with your background in R development and life sciences.
• Chance to contribute to meaningful work in drug discovery, clinical trials, and biomedical research.
• Opportunity to collaborate with leading scientists, bioinformaticians, and data engineers.
• Dedicated time and budget for learning, conferences, and professional growth.
• Work culture centered on autonomy, ownership, and high engineering standards.
• Involvement in impactful tools used by research organizations around the world.

Additional information

This role is advertised on behalf of a partner employer, and that partner manages all applications and subsequent hiring steps. A matching process is used to review applications against the role’s core requirements, and the best-fitting candidates are then shared with the hiring company. The final interview, assessment, and selection process is handled internally by the hiring organization.

Data privacy and application processing

By applying, you agree that the hiring partner may process your personal data to assess your candidacy and share relevant details with the employer. This is done under legitimate interest and pre-contractual measures in line with applicable data protection laws, including GDPR. You may request access, correction, deletion, or objection at any time.

Automated tools may be used to support parts of recruitment, such as reviewing applications, analyzing CVs, or checking responses for possible inconsistencies or verification signals. These tools assist the recruitment team but do not replace human judgment, and final hiring decisions are made by people. If you want more details about data handling, you may contact the employer directly.