This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a R Developer with Life Science Background based in Canada.
This role sits at the intersection of software engineering, data science, and life sciences, focusing on building advanced R-based applications that support critical research in areas such as drug discovery, clinical trials, and biomedical analytics. You will work closely with scientists, bioinformaticians, and data engineers to transform complex biological datasets into interactive, production-grade tools that support real-world scientific and clinical decision-making. The environment is highly collaborative and research-driven, combining strong engineering practices with domain expertise in bioinformatics and biostatistics. You will design and develop scalable Shiny applications and reusable R packages used by global research teams. The role offers deep ownership across the full lifecycle of data-driven applications. It is ideal for someone passionate about both coding and advancing life sciences through technology.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a R Developer with Life Science Background based in Canada.
This role sits at the intersection of software engineering, data science, and life sciences, focusing on building advanced R-based applications that support critical research in areas such as drug discovery, clinical trials, and biomedical analytics. You will work closely with scientists, bioinformaticians, and data engineers to transform complex biological datasets into interactive, production-grade tools that support real-world scientific and clinical decision-making. The environment is highly collaborative and research-driven, combining strong engineering practices with domain expertise in bioinformatics and biostatistics. You will design and develop scalable Shiny applications and reusable R packages used by global research teams. The role offers deep ownership across the full lifecycle of data-driven applications. It is ideal for someone passionate about both coding and advancing life sciences through technology.
Accountabilities:
- Design, develop, and maintain high-quality R and Shiny applications supporting biological and clinical data analysis workflows.
- Process, analyze, and visualize complex life science datasets, ensuring accuracy, reproducibility, and usability of outputs.
- Build and maintain reusable R packages and data processing components to support scalable analytics solutions.
- Collaborate with scientists, bioinformaticians, and stakeholders to gather requirements and translate them into technical solutions.
- Develop and optimize interactive data visualization tools to support research and clinical decision-making.
- Work with version control systems such as Git to manage collaborative development and code quality.
- Contribute to system design discussions, backlog refinement, and continuous improvement of development practices.
- Support deployment and maintenance of production-grade data applications in cloud or distributed environments.
- Strong proficiency in R programming with hands-on experience in production environments.
- Experience working with biological, clinical, or life science data, including data processing, analysis, and visualization.
- Proven experience building web applications using R Shiny or JavaScript.
- Experience creating, maintaining, and documenting R packages.
- Strong understanding of Git and collaborative software development workflows.
- Master’s degree in Bioinformatics, Data Science, Computer Science, Biostatistics, Mathematics, or related field (or equivalent experience).
- Solid understanding of life science concepts such as molecular biology, genomics, or clinical research is highly desirable.
- Ability to translate complex scientific requirements into scalable technical solutions.
- Strong communication and collaboration skills, especially when working with scientific stakeholders.
- Experience with reproducible pipelines, databases, or cloud platforms is a plus.
- Fully remote role with flexible working hours supporting deep work and work-life balance.
- Competitive compensation aligned with experience and expertise in R and life sciences.
- Opportunity to work on meaningful projects in drug discovery, clinical trials, and biomedical research.
- Collaboration with world-class scientists, bioinformaticians, and data engineers.
- Time and budget allocated for continuous learning, conferences, and professional development.
- Strong culture of autonomy, ownership, and engineering excellence.
- Opportunity to contribute to impactful tools used by global research organizations.
Requirements:
Benefits: