Senior Scientist, Biostatistics

United States·Menlo ParkFull-Timesenior

OtherScientist

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Overview

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.

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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.

For more information, please visit grail.com

The Senior Statistical Scientist provides advanced statistical expertise to support research, development, and operational activities across the company. This role involves designing studies, developing analytical strategies, interpreting complex data, and ensuring the scientific rigor of statistical, computational and analytical deliverables. The successful candidate will collaborate cross functionally with lab scientists, data engineers, platform engineers, computational biologists to translate data into meaningful insights that drive evidence-based decisions.

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.

Lead the statistical design, analysis, and interpretation of experiments and studies supporting assay development, validation, and product performance evaluation.
Develop and implement computational and statistical models, data analysis algorithms, and quantitative tools to support research, development, and operational projects. Conduct and communicate complex statistical analyses using appropriate methodologies such as regression, mixed models, nonparametric tests, multivariate methods, and subsampling techniques.
Partner with assay scientists and data engineers to ensure appropriate experimental design and data integrity. Provide statistical input into study protocols, reports, and regulatory submission documents.
Contribute to the development of best practices and standard operating procedures for statistical analyses. Mentor junior scientists and review statistical work to ensure technical accuracy and scientific soundness. Stay current with emerging statistical methodologies, regulatory expectations, and data science innovations.
Demonstrates success in technical proficiency, creativity, collaboration with others and independent thought. Demonstrates ability to work and communicate effectively in a multi-disciplinary study team

Advanced degree (PhD or Master’s) in Statistics, Biostatistics, Bioinformatics, Applied Mathematics, or a related quantitative field.
4+ years of post-PhD or 7+ years of post-MS applying statistical and computational methods, preferably in biotechnology, pharmaceuticals, or diagnostics settings.
Strong knowledge of statistical methodologies such as experimental design, regression, fundamental probability and statistics, Bayesian methods, and multivariate techniques.
Proficiency in statistical programming R. Python is a plus.
Experience with data visualization tools.
Excellent communication skills with the ability to translate complex statistical concepts for non-technical stakeholders.
Proven ability to lead projects independently. Strong problem-solving skills, attention to detail, and ability to manage multiple projects simultaneously.
Experience with assay development, assay performance evaluation, or regulatory submissions is a plus.