Bioinformatics Staff Data Scientist # 4768

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 GRAIL's office or from home. Our current flexible work arrangement policy requires that a minimum of 40%, or 16 hours, of your total work week be on-site. Your specific schedule, determined in collaboration with your manager, will align with team and business needs and could exceed the 40% requirement for the site. At our Menlo Park campus, Tuesdays and Thursdays are the key days where we encourage on-site presence to engage in events and on-site activities., * 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.

• Ph.D. in Bioinformatics, Data Science, Computational Biology, Physics, Bioengineering, Cancer Genomics, Statistics, Biochemistry or a related field with 5+ 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., * 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

Expected full time annual base pay scale for this position is $169,000 - $224,000. 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.

Our mission is to detect cancer early, when it can be cured. We are working to change the trajectory of cancer mortality and bring stakeholders together to adopt innovative, safe, and effective technologies that can transform cancer care. We are a healthcare company, pioneering new technologies to advance early cancer detection. We have built a multi-disciplinary organization of scientists, engineers, and physicians and we are using the power of next-generation sequencing (NGS), population-scale clinical studies, and state-of-the-art computer science and data science to overcome one of medicine's greatest challenges. GRAIL is headquartered in the bay area of California, with locations in Washington, D.C., North Carolina, and the United Kingdom. It is supported by leading global investors and pharmaceutical, technology, and healthcare companies., GRAIL is seeking a Staff Data Scientist to join the Computational Biology team. In this role you will work with population-scale genomic datasets from our on-market commercial product and first-in-class clinical studies to model real-world interactions between technical, biological and clinical factors that underlie current test performance and gain insights into future innovations. You will be developing novel, state-of-the-art methods and tools that will be used to monitor the output of our in-production multi-cancer classifier. Your work will be critical to the success of a new generation of cancer detection products by defining the parameters that ensure a high level of classifier performance over time. The team works cross-functionally across Grail to connect the knowledge behind our advanced cancer detection technology with the clinical variables that define real-world usage as the product scales to large scale adoption. The position is an exciting opportunity at the intersection of machine learning and clinical genomics to support GRAIL's mission to detect cancer early, when it can be cured., GRAIL is a healthcare company whose mission is to detect cancer early, when it can be cured. GRAIL is focused on alleviating the global burden of cancer by developing pioneering technology to detect and identify multiple deadly cancer types early. The company is using the power of next-generation sequencing, population-scale clinical studies, and state-of-the-art computer science and data science to enhance the scientific understanding of cancer biology, and to develop its multi-cancer early detection blood test. GRAIL is headquartered in Menlo Park, CA with locations in Washington, D.C., North Carolina, and the United Kingdom. It is supported by leading global investors and pharmaceutical, technology, and healthcare companies. For more information, please visit www.grail.com.