Senior Data Scientist #4887

Responsibilities

• Analyze complex high-dimensional datasets related to multi-cancer early detection test results from Grail’s commercial platform in order to identify empirical trends and then communicate findings across teams.
• Integrate cancer biology, DNA methylation, genomics, epidemiology, and statistics to generate predictive models of expected test performance and identify potential deviations.
• Participate in cross-functional interactions with interdisciplinary teams including machine learning, software engineering, clinical, laboratory operations, research, and product development.
• Create and communicate rigorous scientific analyses.

Requirements

• Ph.D. in Bioinformatics, Data Science, Computational Biology, Physics, Bioengineering, Cancer Genomics, Statistics, Biochemistry or a related field with 2+ years of relevant experience.
• Proven track record in working with large-scale omics datasets in R (preferred) or Python.
• Experience with NGS data processing, statistical modeling, and machine learning frameworks and their application to derive technical and biological insights in a clinical setting.
• Excellent communication, collaboration, and problem-solving skills; ability to work independently and effectively across interdisciplinary environments.
• Demonstrated ability to perform rigorous and detail-oriented work.

Preferred Qualifications

• Knowledge of cancer epigenetics, cancer biology, tumor genetics, and molecular mechanisms of oncogenesis.
• Experience with traditional ML and modern AI techniques.
• Track record of scientific contributions (e.g., publications, tools, datasets, patents, or conference presentations).
• Proficiency in Python or R, with experience in modern data science workflows (Linux, Git, reproducible pipelines, etc…).
• Interest in translating research innovations into production-ready systems.