Bioinformatics Scientist

When our values align, there's no limit to what we can achieve.
 
At Parexel, we all share the same goal - to improve the world's health. From clinical trials to regulatory, consulting, and market access, every clinical development solution we provide is underpinned by something special - a deep conviction in what we do.

Each of us, no matter what we do at Parexel, contributes to the development of a therapy that ultimately will benefit a patient. We take our work personally, we do it with empathy and we're committed to making a difference.

Parexel is looking for a Bioinformatics Scientist to work with one of our large sponsors. The role is remote based but you must live and have the right to work in one of the following EMEA countries only:
 

United Kingdom

Germany

France

Spain

Romania

Serbia

Lithuania

Poland
 

The Bioinformatics Scientist role will fulfill a computational biology and bioinformatics role that supports analysis, data operations/QC, visualization tools, pipeline automation and cross-study data integration support. The role involves the execution of well-defined requests—such as figure/analysis iterations, running QC data analysis, maintaining data and results viewers, and possible AI assisted analysis code development. The role works within existing analysis plans and technical frameworks, and escalates anything that needs to advance scientific interpretation and presentation.
 

Job Responsibilities: (with minimal supervision)
 

Data Analysis:

• Figure and analysis updates: Support adhoc requests and updates to analyses and outputs such as figures with different splits/subsets, labels, groupings, color palettes, and formatting while preserving the underlying statistical results.

• Pipeline execution: run and optimize automated processing pipelines, perform routine QC on outputs, and document run parameters, versions, and any deviations.

• Data QC / results QC: execute QC checks on data and result deliverables  generate QC summaries, and route issues for resolution.

• Results Data viewers: Build and refresh RMarkdown/Quarto or Shiny data viewers using approved templates for single-study and cross-study exploration; package and publish outputs in the agreed team format.

• Cross-study database integration support: contribute to data collation, standardization, and ingestion activities (mapping variables, harmonizing identifiers, validating joins, running ETL checks)
   

Experiment Preparation:

• Olink randomization: generate balanced layouts using the teams approved algorithm, validate balance metrics and coordinate downstream sample list submission steps.
   

Open Source Code Development

• Claude Code sharing and optimization: maintain a reusable library of prompts/snippets/skills for common tasks (e.g., data viewer creation), define standards (style, testing, documentation), and provide light enablement to ensure consistent AI-assisted workflows.

Job Requirements:

Scientific Background:
 

Knowledge in cardiovascular, metabolic, immunity, hematology, oncology, renal diseases, neurodegenerative disorders, muscle and metabolism disorders, and/or rare genetic diseases.

Technical Skills:

• Open-source programming such as R, R Shiny, and bash

• Using version control tools (git)

• Using Claude Code and other AI tools
   

Other Skills:

• Familiarity with basic statistical modeling fundamentals (linear/logistic models, survival concepts, multiple testing awareness)

• QC mindset and validation

• Good communication and collaboration skills.

• Comfortable with quick paced environment
   

Required Special Equipment and/ or programs:

• R/ R/Python, R Shiny, bash

Required Education:

BS. (MS. is a plus) in Bioinformatics, Computer Science, Computational Biology, Life Sciences, or related discipline with 4+ years of programming experience, preferably in life sciences (cardiovascular, metabolic, immunity, hematology, oncology, renal diseases, neurodegenerative disorders, muscle and metabolism disorders, and/or rare genetic diseases) processing molecular data and or clinical trial data in the biotechnology, pharmaceutical, or health-related industry.