Job Responsibilities:

• 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.

Here are a few requirements specific to this advertised role.

• Bachelor’s degree in life sciences, computer science, data science, bioinformatics, or a related field.

• 2 years+ experience in clinical data, visualization, or analytics

• Spotfire and R Programming experience is a must

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

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

• Able to communicate effectively in English, both in writing and verbally.

The following would also be advantageous:

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

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

• Experience with interactive tools such as Tableau, Power BI, R/Shiny or Python.

• Ability to follow visual design templates and apply style consistency.