GRAIL - Senior Data Scientist # 4630
Requirements
• Ph.D. in Bioinformatics, Computational Biology, Computer Science, Statistics, Machine Learning, or a related field with 2+ years of relevant experience, OR • M.S. with 4+ years of relevant experience, OR • B.S. with 6+ years of relevant experience, or equivalent practical experience • 2+ years of experience applying machine learning or statistical modeling in a research or production environment • Strong expertise in data analysis using Python or R • Deep understanding of modern machine learning and statistical methods • Experience developing reproducible, well-structured code in a collaborative environment • Strong written and verbal communication skills • Experience with modern AI techniques, including deep learning and/or large language model (LLM) training or adaptation • Experience working with sequencing or genomics data and deriving biological insights • Track record of scientific contributions (e.g., publications, tools, datasets, patents, or conference presentations) • Experience with system-level programming languages (e.g., Go, Java, C, C++) • Familiarity with version control (e.g., Git) and reproducible research practices in Linux environments • Demonstrated ability to independently drive projects while collaborating effectively across teams • Interest in translating research innovations into production-ready systems • The expected, full-time, annual base pay scale for this position is 156K - $187K. 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 the terms of the applicable plans and Company discretion. This range reflects a good-faith estimate of the range that the Company reasonably expects to pay for the position upon hire; the actual compensation offered may vary depending on factors such as the candidate’s qualifications. Employees in this role are also eligible for GRAIL’s comprehensive and competitive benefits package, offered in accordance with our applicable plans and policies. This package currently includes flexible time-off or vacation; a 401(k) retirement plan with employer match; medical, dental, and vision coverage; and carefully selected mindfulness programs.
Responsibilities
• Envision, design, and lead projects to evaluate and improve machine learning classifier performance for cancer detection • Collaborate cross-functionally with scientists, engineers, and clinicians to plan, execute, and interpret experiments • Develop high-quality, reproducible, and scalable software aligned with sound engineering principles • Analyze large-scale sequencing and genomics datasets to extract meaningful biological insights • Contribute to the development and evaluation of novel machine learning methods, including deep learning approaches • Communicate findings and present updates regularly in technical and cross-functional forums • Contribute to scientific publications, internal tools, and production systems
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