R Developer with Life Science Background

Overview

This role is for an R developer with a strong life sciences foundation, based in Australia and working remotely. It is offered through a partner company that handles the application review and subsequent hiring stages.

The position blends software engineering, data science, and life sciences. You will help create advanced R-based tools that support research in areas such as drug discovery, clinical trials, and biomedical analytics. The work is highly collaborative and research-led, with close interaction with scientists, bioinformaticians, and data engineers. A key part of the job is turning complex biological data into reliable, production-ready applications that can support scientific and clinical decisions.

You will take ownership of the full development lifecycle for data-driven applications, including design, development, deployment, and ongoing maintenance. The role is well suited to someone who enjoys both programming and contributing to life sciences through technology.

Responsibilities

• Create, enhance, and support robust R and Shiny applications used for biological and clinical data analysis.
• Clean, analyze, and present complex life science datasets while maintaining accuracy, repeatability, and user-friendly outputs.
• Develop reusable R packages and data-processing building blocks that can scale across analytics projects.
• Partner with scientists, bioinformaticians, and other stakeholders to understand needs and convert them into technical solutions.
• Build and improve interactive visualizations that help with research and clinical decision-making.
• Use Git and related version-control practices to support team-based development and maintain code quality.
• Take part in system design conversations, backlog grooming, and ongoing improvements to development workflows.
• Help deploy and maintain production-level data applications in cloud-based or distributed setups.

Requirements

• Strong command of R, with practical experience using it in production settings.
• Background working with biological, clinical, or life science data, including data preparation, analysis, and visualization.
• Experience developing web applications with R Shiny or JavaScript.
• Track record of creating, maintaining, and documenting R packages.
• Good working knowledge of Git and collaborative software development processes.
• Master’s degree in Bioinformatics, Data Science, Computer Science, Biostatistics, Mathematics, or a closely related discipline, or equivalent experience.
• Working knowledge of life science topics such as molecular biology, genomics, or clinical research is strongly preferred.
• Ability to translate complex scientific needs into scalable technical solutions.
• Strong communication and teamwork skills, especially when working with scientific experts.
• Experience with reproducible workflows, databases, or cloud platforms is an added advantage.

Perks

• Fully remote setup with flexible hours that support focus time and better work-life balance.
• Competitive pay aligned with experience and domain expertise in R 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.
• Allocated time and budget for learning, conferences, and professional growth.
• A culture that values autonomy, ownership, and engineering quality.
• The ability to help build tools used by research organizations around the world.

Additional Information

This listing is managed by a partner company, which is responsible for application handling and the next steps in the hiring process.

The hiring process uses an AI-assisted matching approach to review applications against the role’s core requirements and generate a shortlist for the employer. Final decisions and further steps, such as interviews or assessments, are handled by the hiring company’s internal team.

By applying, candidates agree that their personal data may be processed for recruitment purposes and shared with the hiring employer under applicable data protection rules, including GDPR where relevant. Applicants may request access to, correction of, deletion of, or objection to the use of their data at any time.

AI tools may also be used to support parts of the recruitment workflow, such as reviewing applications, analyzing resumes, and checking for inconsistencies or verification signals. These tools assist recruiters but do not replace human judgment, and final hiring decisions are made by people.