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Data Scientistprinceps technologiees • Toronto, ON, ca
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Data Scientist

Data Scientist

princeps technologiees • Toronto, ON, ca
5 hours ago
Job type
  • Full-time
Job description

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 GitHub/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/GitHub.
  • 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.



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 GitHub/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/GitHub. 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.

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Data Scientist • Toronto, ON, ca