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Über
Our mission is to detect cancer early, when it can be cured. We are a healthcare company pioneering new technologies to advance early cancer detection, using next-generation sequencing (NGS), population-scale clinical studies, and state-of-the-art data science to transform cancer care. GRAIL is headquartered in the Bay Area, with locations in Washington, D.C., North Carolina, and the United Kingdom. For more information, please visit grail.com. We are seeking a Data Scientist with strong expertise in cancer genomics and omics data modeling to help drive the next wave of innovation in early cancer detection. In this role, you will analyze large genomic and real-world datasets to uncover biological signals, model cancer biology, and identify genomic features that improve test performance. You will apply statistical and machine learning methods to extract insights from multi-omic data and translate them into actionable improvements and new products for clinical oncology applications. The ideal candidate combines deep knowledge of cancer genomics with practical experience in statistical inference and machine learning model development. You will work cross-functionally with computational biologists, assay scientists, machine learning and data engineers, and clinical experts to accelerate innovation and strengthen test performance. This role is based in Menlo Park, California, and will move to Sunnyvale, California, in Fall 2026. It offers a flexible work arrangement, with the ability to work from the office or from home. A minimum of 40% (16 hours) on-site per total work week is required, with schedule determined in collaboration with your manager and may exceed 40% to meet team needs. On-site presence is encouraged on Tuesdays and Thursdays at the Menlo Park campus. Responsibilities
Analyze and interpret large-scale NGS datasets to identify biological and molecular patterns related to cancer detection Design, implement, and validate innovative statistical methods and machine learning models to extract and interpret cancer genomic signals for product innovation Collaborate with interdisciplinary teams to translate data-driven insights into actionable decisions Present and communicate high-quality, evidence-based research findings with clarity and rigor Required Qualifications
Ph.D. in Cancer Genomics, Statistics, Bioinformatics, Computational Biology, Data Science, Engineering or a related field Proven track record working with large-scale omics datasets in R or Python Expertise in genomics with hands-on experience in genomics technologies and analysis methods Familiarity with NGS data processing, statistical modeling, and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Excellent communication, collaboration, and problem-solving skills; ability to work effectively in interdisciplinary environments Preferred Qualifications
Experience in hematological oncology research Knowledge of cancer epigenetics Strong knowledge of cancer biology, tumor genetics, and molecular mechanisms of oncogenesis Ability to integrate biological knowledge with computational modeling to uncover new insights or create tools Deep understanding of modern machine learning fundamentals and AI techniques for genomics, including model development, evaluation, and interpretation Experience with deep learning and/or large language model (LLM) training or adaptation Proficiency in Python or R with experience in modern data science workflows (Linux, version control, reproducible pipelines) Compensation and Benefits
The expected, full-time, annual base pay scale for this position is $136K - $167K. Actual base pay will consider skills, experience, and location. This role may be eligible for other forms of compensation, including an annual bonus and/or incentives, subject to applicable plans and company discretion. Employees are eligible for a comprehensive benefits package, including flexible time-off or vacation; a 401(k) retirement plan with employer match; medical, dental, and vision coverage; and mindfulness programs. Equal Employment Opportunity
GRAIL is an equal employment opportunity employer and is committed to building a workplace where every individual can thrive, contribute, and grow. All qualified applicants will receive consideration without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, age, disability, status as a protected veteran, or any other class or characteristic protected by applicable laws. GRAIL will consider qualified applicants with arrest and conviction records in a manner consistent with applicable law and provide reasonable accommodations to qualified individuals with disabilities. For accommodations to apply, please contact rc@grailbio.com. GRAIL maintains a drug-free workplace and welcomes job-seekers from all backgrounds.
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- English
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