Key Responsibilities
• Design, develop, and deploy scalable machine learning models to predict patient outcomes and biomarker associations in oncology trials.
• Lead end‑to‑end data engineering workflows, integrating multi‑omics, imaging, and electronic health record data into unified analytical platforms.
• Collaborate with cross‑functional teams (clinical, regulatory, product) to translate analytical findings into actionable clinical strategies.
• Mentor and coach junior data scientists, fostering a culture of rigorous statistical practice and reproducible research.
• Present complex insights to senior leadership, translating technical results into clear business and clinical impact.

Requirements
• PhD or MS in Statistics, Bioinformatics, Computer Science, or related field with 10+ years of industry experience.
• Expertise in Python, R, and SQL for data manipulation, model building, and performance optimization.
• Proven track record of deploying ML models in a regulated environment, with familiarity of FDA/EMA guidelines.
• Strong background in biostatistics, survival analysis, and clinical trial design.
• Excellent communication skills and ability to influence stakeholders across scientific and business domains.