ICON

Clinical Data Scientist

In short

Senior Clinical Data Scientist/Statistical Programmer role at ICON, a large FSP organisation serving pharma/biotech sponsors, working in a hybrid, sponsor-dedicated model. The job centers on designing and maintaining R Shiny applications for clinical study monitoring, safety review, and data visualization, alongside CDISC (SDTM/ADaM) compliant statistical programming. Requires 5+ years of statistical programming experience in pharma/biotech/CRO and strong R Shiny/CDISC expertise.

Clinical Data Scientist
At ICON Strategic Solutions, you will work in a sponsor-dedicated model, supported by ICON's global expertise. As the world's largest FSP organisation, with over 90 sponsor partnerships, we offer stability, career development and a collaborative environment where your work contributes to the development of treatments that benefit patients worldwide.
We are seeking a highly skilled Clinical Data Scientist/Senior Statistical Programmer with extensive experience in R Shiny application development and a strong background in clinical trial data standards. This role is ideal for someone who enjoys building user-centric analytical tools, transforming complex datasets into intuitive interactive dashboards, and driving high-quality statistical outputs in accordance with industry standards. You will collaborate closely with statisticians, data managers, clinical programmers, and project leads to design, develop, and maintain innovative R-based solutions that support study monitoring, data review, and analytical insight generation across clinical development programmes.
Responsibilities
•Design, build, and maintain R Shiny applications for clinical study monitoring, data visualization, safety review, and exploratory analysis.
•Develop modular, scalable, and well-documented R code following best practices.
•Create interactive dashboards, visualizations, and bespoke analytical tools for cross-functional teams.
•Optimize Shiny app performance, security, and usability for deployment in regulated environments.
•Ensure all deliverables comply with CDISC standards, regulatory guidance, and internal SOPs.
•Act as a subject matter expert (SME) for R and R Shiny within the team.
•Mentor junior programmers and contribute to knowledge-sharing initiatives.
•Participate in study meetings, providing technical insights and programming expertise.
•Influence best practices, pipelines, and automation strategies for modernizing statistical workflows.
Requirements
•5+ years of experience as a Statistical Programmer within the pharmaceutical/biotech/CRO industry.
•Strong clinical data experience, including CDISC (SDTM & ADaM) and TLF production.
•R Shiny experience, including: end-to-end app development, UI/UX design, dashboard visualizations (ggplot2/plotly), performance optimization and debugging.
•Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, or a related field.
•Experience with Python, SAS, or other analytical tools.
•Familiarity with pharmacovigilance or safety review workflows.
•Experience with Real World Evidence data.
•Experience deploying R Shiny apps (Shiny Server, Posit Connect, etc.).
•Exposure to automation, data engineering, or cloud environments.
Conditions
•Opportunity to lead innovation in R-based analytics.
•Collaborative and forward-thinking team environment.
•Competitive salary and benefits package.
•Career development and access to modern tools and training.
•Ability to influence strategy around R Shiny and data visualization initiatives.
•Employment with ICON is contingent upon having the legal right to work in the country where the role is based.
•Competitive base salary and performance related incentives.
•Health and wellbeing programmes including medical, dental, and vision coverage where applicable.
•Retirement and pension plans.
•Life assurance and disability coverage.
•Employee assistance programmes and wellbeing resources.
•Learning and development opportunities through structured training and career pathways.
•Benefits may vary depending on role and location.

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