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Salary: USD 188,275 - 270,375 / annual
Freenome is seeking a Staff Computational Biologist to join the Computational Biology, Assay Research (CBAR) team and drive the development of early, noninvasive cancer detection tests. This is a senior individual contributor role that reports to a Manager and Senior Staff Computational Biologist.
You will apply deep expertise in NGS assay development, bioinformatics, statistics, and molecular biology to design and execute research studies for prototype cancer early detection products using cfDNA biomarkers. Working cross-functionally with Molecular R&D, Model R&D, and Computational Biology teams, you will serve as a key thought leader on the computational science team.
Key responsibilities include: leading analysis and interpretation of molecular and clinical data in early cancer detection contexts; proposing research hypotheses and computational improvements, then planning and executing associated research projects from ideation through implementation; developing bioinformatics pipelines for high-throughput NGS data processing and analysis; collaborating with wet lab scientists to characterize and iterate on experimental methods through real-time assay performance assessment; and staying current with molecular oncology techniques to advance next-generation early detection assays.
Required qualifications: PhD in computational biology, cancer biology, statistics, bioinformatics, or related quantitative field; 6+ years of industry experience applying computational techniques for biological discovery and product development, ideally in cancer or diagnostics; extensive NGS assay and pipeline development experience with demonstrated track record implementing complex workflows for high-throughput data processing; strong quantitative reasoning and data analysis skills; proficiency in Python (NumPy, Matplotlib, Pandas) or equivalent languages like R; excellent communication skills for scientific and broader audiences; and ability to thrive in a collaborative, cross-functional environment.
Nice-to-have qualifications include expert knowledge of chromatin biology, liquid biopsy, DNA methylation in cancer early detection; extensive DNA methylation data experience; and background developing and evaluating statistical or machine learning algorithms.
