
10,000+ employees
Founded 1983
đŒ Consulting
đ„ Healthcare
đŠ Logistics
đ° Venture Round on 1990-01
Consulting âą Healthcare âą Logistics
Parexel is one of the world's largest clinical research organizations (CROs), providing comprehensive services for the clinical development process from Phase I to IV. The company specializes in portfolio management, clinical trial management, regulatory strategy, market access, and lifecycle management for biopharmaceuticals. Parexel aims to speed life-changing medicines to market by leveraging its clinical, regulatory, and therapeutic expertise. With a global team of over 21,000 professionals, Parexel works to integrate patient insights and innovative trial designs to develop treatments across therapeutic areas such as oncology, neuroscience, rare diseases, and more. It focuses on delivering patient-centric and efficient clinical trials.
đ„ 0 minutes ago
đ United Kingdom, Germany, +6 more countries â Remote
â° Full Time
đĄ Mid-level
đ Senior
đŹđ§ UK Skilled Worker Visa Sponsor
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10,000+ employees
Founded 1983
đŒ Consulting
đ„ Healthcare
đŠ Logistics
đ° Venture Round on 1990-01
Consulting âą Healthcare âą Logistics
Parexel is one of the world's largest clinical research organizations (CROs), providing comprehensive services for the clinical development process from Phase I to IV. The company specializes in portfolio management, clinical trial management, regulatory strategy, market access, and lifecycle management for biopharmaceuticals. Parexel aims to speed life-changing medicines to market by leveraging its clinical, regulatory, and therapeutic expertise. With a global team of over 21,000 professionals, Parexel works to integrate patient insights and innovative trial designs to develop treatments across therapeutic areas such as oncology, neuroscience, rare diseases, and more. It focuses on delivering patient-centric and efficient clinical trials.
âą Support ad hoc requests and updates to analyses and outputs, including figures with different splits/subsets, labels, groupings, color palettes, and formatting while preserving underlying statistical results âą Run and optimize automated processing pipelines, perform routine QC on outputs, and document run parameters, versions, and deviations âą Execute QC checks on data and result deliverables, generate QC summaries, and route issues for resolution âą Build and refresh RMarkdown/Quarto or Shiny data viewers using approved templates for single-study and cross-study exploration âą Package and publish data viewer outputs in the agreed team format âą Support cross-study database integration through data collation, standardization, ingestion, variable mapping, identifier harmonization, join validation, and ETL checks âą Generate balanced Olink randomization layouts using the teamâs approved algorithm âą Validate Olink balance metrics and coordinate downstream sample list submission steps âą Maintain a reusable library of Claude Code prompts, snippets, and skills for common tasks âą Define standards for AI-assisted workflows, including style, testing, and documentation âą Provide light enablement to support consistent AI-assisted workflows âą Work with minimal supervision within existing analysis plans and technical frameworks âą Escalate matters requiring advances in scientific interpretation and presentation
âą BS in Bioinformatics, Computer Science, Computational Biology, Life Sciences, or related discipline required âą 4+ years of programming experience âą Preferably experience in life sciences processing molecular data and/or clinical trial data in the biotechnology, pharmaceutical, or health-related industry âą Knowledge in cardiovascular, metabolic, immunity, hematology, oncology, renal diseases, neurodegenerative disorders, muscle and metabolism disorders, and/or rare genetic diseases âą Experience with open-source programming such as R, R Shiny, and bash âą Experience using version control tools such as git âą Experience using Claude Code and other AI tools âą Familiarity with basic statistical modeling fundamentals, including linear/logistic models, survival concepts, and multiple testing awareness âą QC mindset and validation âą Good communication and collaboration skills âą Comfortable with a quick-paced environment âą Required equipment/programs: R/R/Python, R Shiny, bash
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