Job Description We are seeking a Data Scientist with strong clinical trial domain knowledge, particularly in oncology , to join our Global Biostatistics team.

This role combines clinical data science, statistical programming, and study-level support to help teams analyze, visualize, and interpret clinical trial data through advanced analytics platforms.

The successful candidate will independently manage day-to-day analytical activities for assigned studies, ensuring efficacy and safety objectives are met.

Requirements Key Responsibilities Study Support: Serve as the Data Science lead for assigned clinical studies, collaborating with statisticians and programmers to meet analytical needs and milestones.

Oncology Analysis: Support efficacy analyses (PFS, OS, ORR, BOR, DCR, and time-to-event endpoints) and safety analyses (AEs, TEAEs, lab abnormalities, and dose modifications).

Programming & Data: Use R for clinical data manipulation and analysis.

Work with CDISC standards (SDTM/ADaM) and manage code via Git

Hub/Git-based version control .

Visualization: Develop clinical visualizations including swimmer plots, waterfall plots, time-to-event displays , and interactive dashboards/patient profiles.

Clinical Interpretation: Apply knowledge of RECIST 1.1 and study protocols to ensure analytical outputs are clinically meaningful and accurate.

Automation: Identify opportunities to automate reporting activities and reuse code across studies to improve efficiency.

Required Qualifications & Experience Education: Bachelor’s or master’s degree in a quantitative or life sciences field (e.g., Biostatistics,



Bioinformatics, Data Science).

Experience: 3-5+ years in a pharmaceutical or biotech environment working with clinical trial data.

Technical Skills: Expert-level R programming and proficiency with Git/Git

Hub .

Domain Knowledge: Deep understanding of the clinical development lifecycle and oncology-specific endpoints (PFS, ORR, OS, etc.).

Data Standards: Solid working knowledge of SDTM and ADaM datasets.

Communication: Ability to translate complex statistical requirements into actionable analytical solutions and communicate effectively with cross-functional study leads.

Preferred Qualifications Experience with R/Shiny for interactive clinical data review.

Specific experience in solid tumor oncology trials.

Familiarity with automation and building reusable programming frameworks.

Requirements Key Responsibilities Study Support: Serve as the Data Science lead for assigned clinical studies, collaborating with statisticians and programmers to meet analytical needs and milestones.

Oncology Analysis: Support efficacy analyses (PFS, OS, ORR, BOR, DCR, and time-to-event endpoints) and safety analyses (AEs, TEAEs, lab abnormalities, and dose modifications).

Programming & Data:



Use R for clinical data manipulation and analysis.

Work with CDISC standards (SDTM/ADaM) and manage code via Git

Hub/Git-based version control.

Visualization: Develop clinical visualizations including swimmer plots, waterfall plots, time-to-event displays, and interactive dashboards/patient profiles.

Clinical Interpretation: Apply knowledge of RECIST 1.1 and study protocols to ensure analytical outputs are clinically meaningful and accurate.

Automation: Identify opportunities to automate reporting activities and reuse code across studies to improve efficiency.

Required Qualifications & Experience Education: Bachelor’s or master’s degree in a quantitative or life sciences field (e.g., Biostatistics, Bioinformatics, Data Science).

Experience: 3-5+ years in a pharmaceutical or biotech environment working with clinical trial data.

Technical Skills: Expert-level R programming and proficiency with Git/Git

Hub.

Domain Knowledge: Deep understanding of the clinical development lifecycle and oncology-specific endpoints(PFS, ORR, OS, etc.).

Data Standards: Strong working knowledge of SDTM and ADaM datasets.

Communication: Ability to translate complex statistical requirements into actionable analytical solutions and communicate effectively with cross-functional study leads.

Preferred Qualifications Experience with R/Shiny for interactive clinical data review.

Specific experience in solid tumor oncology trials.

Familiarity with automation and building reusable programming frameworks.

📌 Data Scientist (Toronto)
🏢 Princeps Technologiees
📍 Toronto