Senior Scientist, Biostatistics

Grail•Menlo Park, CA

1d•Hybrid

About The Position

GRAIL is a healthcare company pioneering new technologies to advance early cancer detection. Our mission is to detect cancer early, when it can be cured, and we are working to change the trajectory of cancer mortality. We have built a multi-disciplinary organization of scientists, engineers, and physicians, utilizing next-generation sequencing (NGS), population-scale clinical studies, and state-of-the-art computer and data science. The Senior Statistical Scientist will provide advanced statistical expertise to support research, development, and operational activities. 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, and 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, requiring a minimum of 40% (16 hours) on-site per week. Tuesdays and Thursdays are encouraged on-site days for engagement.

Requirements

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.

Nice To Haves

Experience with assay development, assay performance evaluation, or regulatory submissions is a plus.

Responsibilities

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.