About this 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

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.

Data Scientist

Key skills