Grail

Senior Data Scientist #4887

Grail$156K — $187K *
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Ph.D. in Bioinformatics, Data Science, Computational Biology, Physics, Bioengineering, Cancer Genomics, Statistics, Biochemistry, or related field with 2+ years of experience.
  • Proficiency in working with large-scale omics datasets, primarily using R or Python.
  • Experience in NGS data processing, statistical modeling, and machine learning in clinical applications.
  • Strong communication and collaboration skills to work across interdisciplinary teams.
  • Demonstrated attention to detail and the ability to conduct rigorous scientific analysis.

Responsibilities

  • Analyze complex high-dimensional datasets from multi-cancer early detection tests to identify trends.
  • Integrate knowledge of cancer biology, genomics, and statistics to create predictive models for test performance.
  • Engage in cross-functional teamwork with machine learning, software engineering, and clinical operations.
  • Develop and communicate scientific analyses clearly across departments.

Benefits

  • Flexible time-off or vacation policy.
  • 401(k) retirement plan with employer match.
  • Comprehensive medical, dental, and vision coverage.
  • Access to mindfulness programs designed for employee wellness.
  • Flexible work arrangements with a minimum on-site requirement.
Full Job Description
GRAIL is seeking a Senior 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.

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.

Responsibilities:

  • 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.


Required Qualifications:

  • Ph.D. in Bioinformatics, Data Science, Computational Biology, Physics, Bioengineering, Cancer Genomics, Statistics, Biochemistry or a related field with 2+ 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.


Preferred Qualifications:

  • 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


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.

About Grail

Grail is a healthcare company that develops and commercializes blood tests for early cancer detection. The company's tests use a combination of machine learning, genomics, and clinical data to detect cancer at an early stage, when it is most treatable. Grail was founded in 2016 and is headquartered in Redwood City, California.
Learn more about Grail
Size
500 employees
Industry
Founded
2016

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