Data Scientist

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.