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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