R / R Shiny Programmer (Real-time Visual Analytics Specialist / Senior Data Scientist)

Remote Full-time
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.

The Real-time Visual Analytics Specialist in Early Development Biometrics is responsible for designing, delivering, and maintaining interactive, study-level data visualizations that support Medical Data Review (MDR) and safety signal detection. Operating at the intersection of data science, clinical research, and digital enablement, this role ensures that visual analytics are aligned with Risk-Based Quality Management (RBQM) principles, defined Critical to Quality (CtQ) factors, and Medical Data Review Plans (MDRPs).

Required experience and skills which are essential to qualify for this role:
Hold a Bachelor’s degree in life sciences, computer science, data science, bioinformatics, or a related field

Have 1-3 years of experience in clinical data, visualization, or analytics; or an advanced degree with 1-3 years of equivalent work experience

Proficient in tools including R Shiny & Git

Experienced with programming languages including R and tidyverse

Have a basic understanding of clinical trial data and common data structures (e.g., CRF data)

Demonstrate strong attention to detail, logical thinking, and an eagerness to learn visualization standards and clinical workflows

Show respect for cultural differences when interacting with colleagues in the global workplace

Communicate effectively in English, both in writing and verbally


Preferred skills:
Exposure to clinical or safety data structures and terminology (e.g., adverse events, lab results, dosing)

Experience with:

R package development

R Teal

Developer experience with R shiny

Claud code

Familiarity with Risk-Based Quality Management (RBQM) concepts and their role in early development

Interest in visual storytelling and user experience in data interpretation

Ability to follow visual design templates and apply style consistency

Curiosity and willingness to learn visualization standards and workflows in a regulated environment

Role KPA'S & day-to-day activities include:

The Real-time Visual Analytics Specialist will create standardized yet customizable data visualization templates and provide study teams with high-impact graphical tools to support early development decision-making. Will also serve as a partner and point of support for clinical scientists, offering training and ongoing consultation to ensure effective use of visual analytics in study workflows. With an eye toward scalability, compliance, and scientific relevance, the Real-time Visual Analytics Specialist plays a critical role in accelerating insight generation across exploratory and safety-critical endpoints.
Create and maintain standardized data visualizations to support Medical Data Review and safety signal detection, following established templates and guidance

Apply defined visualization standards to generate outputs aligned with Risk-Based Quality Management (RBQM) principles and Critical to Quality (CtQ) endpoints

Work under guidance to implement visual analytics within timelines tied to First Patient In (FPI) or predefined safety milestones

Support documentation and quality control of visualization deliverables to ensure traceability and compliance

Participate in training sessions and incorporate feedback from more experienced Real-time Visual Analytics Specialists

Assist in responding to basic stakeholder requests and clarifying data availability or visualization functionality

Work under general supervision and apply independent judgment to interpret guidance, prioritize responsibilities, and make decisions in situations that require contextual understanding

Apply judgment to address moderately complex statistical or data issues, balancing scientific rigor with appropriate flexibility, and seek guidance when facing novel or ambiguous situations

Adhere to functional standards by participating in peer review and mentoring relationships to uphold quality and build methodological and regulatory expertise

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