Remote Bioinformatics Scientist—R/Shiny & AI Analysis

Parexel; Uxbridge; On-site; GBP 60,000 - 90,000; Full time

Job summary

Parexel is seeking a Bioinformatics Scientist to join a remote role across eligible EMEA countries. You will support analysis, data operations/QC, visualization tools, and pipeline automation within established analysis plans.

The role emphasizes cross-study data integration and AI-assisted coding. Responsibilities include data analysis updates, pipeline execution, QC, and building data viewers using RMarkdown, Quarto, or Shiny.

Qualifications

• BS or MS in bioinformatics, computational biology, life sciences or related field.
• 4+ years of programming experience in life sciences.
• Knowledge of data visualization and cross-study data integration.
• Open-source programming with R, R Shiny, and bash.
• Experience with git and AI-assisted coding tools.

Responsibilities

• Data Analysis: update figures, run analyses, and ensure statistical integrity.
• Pipeline execution: run automated processes, document parameters and deviations.
• Data QC: perform QC checks and generate summaries; route issues for resolution.
• Data viewers: build/refresh Shiny or RMarkdown viewers for single and cross-study work.
• Cross-study integration: assist data collation, harmonization, and ETL checks.
• Experiment prep: perform Olink randomization and coordinate sample lists.
• Open source coding: maintain reusable AI workflow prompts and snippets.

Skills

R

R Shiny

Bash

Git

Claude Code

AI tools

Statistical modeling

Data QC

Communication

Education

BS/MS in Bioinformatics / Computational Biology / Life Sciences

Tools

R

R Shiny

Bash

Job description

Parexel is seeking a Bioinformatics Scientist to join a remote role across eligible EMEA countries. You will support analysis, data operations/QC, visualization tools, and pipeline automation within established analysis plans.

The role emphasizes cross-study data integration and AI-assisted coding. Responsibilities include data analysis updates, pipeline execution, QC, and building data viewers using RMarkdown, Quarto, or Shiny.