Key Responsibilities
• Design, develop, and deploy scalable machine learning models to predict patient outcomes and identify therapeutic targets in oncology.
• Collaborate with cross‑functional teams to integrate genomic, imaging, and clinical data into unified analytical pipelines.
• Lead data curation, feature engineering, and statistical analysis to support biomarker discovery and trial enrichment strategies.
• Mentor junior data scientists and provide technical guidance on best practices in model validation and reproducibility.
• Communicate findings to stakeholders through clear visualizations, reports, and presentations.

Requirements
• PhD or Master’s in Bioinformatics, Statistics, Computer Science, or related field with 8+ years of industry experience.
• Expertise in Python, SQL, and deep learning frameworks (TensorFlow/PyTorch) for large‑scale biomedical data.
• Strong background in biostatistics, survival analysis, and clinical trial design.
• Proven track record of publishing peer‑reviewed research or delivering production‑grade models in a regulated environment.
• Excellent communication skills and ability to translate complex analytics into actionable insights.