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About the Role

ICON is a global healthcare intelligence and clinical research organisation united by a mission to bring new medicines and treatments to patients faster. As a values-driven organisation, integrity, collaboration, agility, and inclusion are at the heart of how we work and interact with each other, customers, patients and suppliers. 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.

Skills

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.

Experience Level

5+ years of experience as a Statistical Programmer

Education Level

Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, or a related field

Salary/Compensations

Competitive salary and benefits package
Competitive base salary and performance related incentives

Benefits

Opportunity to lead innovation in R‑based analytics.
Collaborative and forward‑thinking team environment.
Career development and access to modern tools and training.
Ability to influence strategy around R Shiny and data visualization initiatives.
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.

About the Company

ICON is a global healthcare intelligence and clinical research organisation.
ICON is an award-winning workplace dedicated to delivering new medicines and medical devices to patients worldwide.
The company is diverse, cares about the world, conducts business sustainably, and supports local communities.

Equal Opportunity

ICON is an equal opportunity employer.
Committed to building an inclusive and accessible workplace where everyone feels valued and supported.
Reasonable accommodations are available during the recruitment process upon request.