R Developer with Life Science Background

Jobgether • United Arab Emirates

Remote

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AI Summary

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. Collaborate with scientists, bioinformaticians, and stakeholders to gather requirements and translate them into technical solutions.

Key Highlights

Design, develop, and maintain high-quality R and Shiny applications

Process, analyze, and visualize complex life science datasets

Collaborate with scientists, bioinformaticians, and stakeholders

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Key Responsibilities

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

Collaborate with scientists, bioinformaticians, and stakeholders to gather requirements and translate them into technical solutions

Technical Skills Required

R Shiny Git

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Benefits & Perks

Fully remote role with flexible working hours

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

Job Description

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.

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