GRAIL
Senior Data Scientist # 4630
Menlo Park, CA · Senior · Full-time
Sponsorship not specified$156k-$187kDetected 123 days ago
PythonJavaGoC++GitLinuxMachine LearningDeep LearningData AnalysisData ScienceNLPLLMsStatisticsClinical TrialsBioinformaticsNGSResearchCommunicationCollaborationPublic Speaking
About the role
- 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 GRAIL is seeking a Senior Data Scientist to join the Machine Learning team within the Computational Biology and Machine Learning (CBML) group.
Responsibilities
- 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
- Experience developing reproducible, well-structured code in a collaborative environment
Requirements
- Strong expertise in data analysis using Python or R
Nice to have
- 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
- Interest in translating research innovations into production-ready systems
- 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.
- and carefully selected mindfulness programs.
Compensation
- The expected, full-time, annual base pay scale for this position is 156K - $187K.
Benefits
- Envision, design, and lead projects to evaluate and improve machine learning classifier performance for cancer detection
- Apply best practices in machine learning and statistics to generate robust, interpretable, and reliable results
- Contribute to the development and evaluation of novel machine learning methods, including deep learning approaches
- Ph.D. in Bioinformatics, Computational Biology, Computer Science, Statistics, Machine Learning, or a related field with 2+ years of relevant experience, OR
- 2+ years of experience applying machine learning or statistical modeling in a research or production environment
- Deep understanding of modern machine learning and statistical methods
This listing is sourced directly from GRAIL's careers page and normalized into a canonical job model.