GRAIL

Data Scientist

GRAIL

full-time

Posted on:

Location Type: Hybrid

Location: Menlo Park • United States

Visit company website

Explore more

✨ AI Apply
Apply

Tech Stack

PythonPyTorchScikit-LearnTensorflow

About the role

  • Analyze and interpret large-scale NGS datasets to identify biological and molecular patterns of cancers related to cancer detection
  • Design, implement and validate innovative statistical methods and machine learning models to extract and interpret cancer genomic signals for product innovation
  • Work closely with interdisciplinary teams (computational, clinical, assay development, and product) to translate data-driven insights to actionable decisions
  • Present and communicate high-quality, evidence-based research findings with clarity and rigor

Requirements

  • Ph.D. in Cancer Genomics, Statistics, Bioinformatics, Computational Biology, Data Science, Engineering or a related field.
  • Proven track record in working with large-scale omics datasets in R or Python.
  • Proven expertise in cancer genomics — excellent knowledge of cancer biology, tumor genetics, and molecular mechanisms of oncogenesis.
  • Familiarity with NGS data processing, statistical modeling, and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
  • Excellent communication, collaboration, and problem-solving skills; ability to work effectively in interdisciplinary environments.
Benefits
  • flexible time-off or vacation
  • a 401(k) retirement plan with employer match
  • medical, dental, and vision coverage
  • carefully selected mindfulness programs
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
NGS data analysisstatistical methodsmachine learning modelsdata interpretationRPythonstatistical modelingcancer genomicstumor geneticsmolecular mechanisms
Soft Skills
communicationcollaborationproblem-solvinginterdisciplinary teamworkclarity in presentationevidence-based research
Certifications
Ph.D. in Cancer GenomicsPh.D. in StatisticsPh.D. in BioinformaticsPh.D. in Computational BiologyPh.D. in Data SciencePh.D. in Engineering