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Parexel

Senior Associate Biomarker Data Scientist

Reposted 6 Days Ago
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In-Office or Remote
Hiring Remotely in Spain
Senior level
In-Office or Remote
Hiring Remotely in Spain
Senior level
Supports biomarker data science workflows by running, maintaining, and improving R-based analysis pipelines, packages, templates, and flow cytometry gating workflows. Manages data intake, harmonization, documentation, quality control, reproducibility, and deliverable tracking. Contributes to Git-based development and reusable Claude Code libraries, including standards for testing, documentation, and AI-assisted coding. Collaborates with scientists and operational teams on clinical and molecular data analyses.
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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 Senior Associate Biomarker Data 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

France

Spain

Romania

Serbia

Lithuania

Poland

The Senior Associate Biomarker Data Scientist is a quantitative data science role that supports analysis, pipeline execution, maintenance, and enhancements to established biomarker analytics workflows. The role may also assist in the development of tools for operational program tracking and shared AI-assisted coding standards. The position may also involve running and tuning existing pipelines (including flow cytometry automated gating), and well-scoped improvements to ensure deliverables and analyses are delivered on time.

Job Responsibilities:

Pipeline and R Package Development:

  • Runs, monitors, and maintain existing analysis pipelines, internal R packages and report templates including interactive data exploration tools

  • Version control & collaboration: contribute via git (branching, pull requests, code review), and coordinate handoffs.

Data Operations And QC

  • Manage end-to-end data flow: requesting data from BDM, tracking delivery, organizing on internal servers with proper folder structure and data cut documentation.

  • Prepare and send sample lists to sample management and other departments upon request

  • Works with scientists to harmonize heterogeneous formats, for the ongoing ingestion of biomarker data into common data formats

  • Reproducibility & QC: maintain run logs, validate outputs against expected formats/metrics, and ensure raw vs processed outputs are stored according to team conventions.

  • Support project & deliverable trackers: maintain a robust tracking system for analysis/pipeline deliverables (status, owners, due dates, dependencies, links to locations), and provide concise visibility for stakeholders.

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:

  • 2+ years of programming experience, preferably in life sciences processing molecular data and or clinical trial data in the biotechnology, pharmaceutical, or health-related industry.

  • Experience running and maintaining genomic pipelines

Technical Skills

  • Experience in open-source programming such as R, R Shiny, and bash

  • Experience using version control tools (git)

  • Experience using Claude Code and other AI tools

  • SQL, database design (PostgreSQL/similar), ETL pipelines

  • HTML/CSS/JavaScript basics

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 fast paced environment

Required Education

BS. (MS. is a plus) in Bioinformatics, Computer Science, Computational Biology, Life Sciences, or related discipline.

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