Lead Bioinformatics & Machine Learning Scientist

Role overview Develop machine learning methods for cancer detection in a minimal residual disease setting using sequencing and methylation data. This senior research role spans algorithm design, end-to-end analysis, and collaboration with experimental scientists as assay needs evolve. The work requires careful evaluation of model performance and reliable handling of high-volume data across cohorts and clinical protocols.

Responsibilities - Design, train, and evaluate machine learning models that support cancer detection and treatment-related decisions. - Lead analyses from research question through implementation, troubleshooting, and performance assessment. - Extend existing computational pipelines and develop new analytical features. - Connect experimental design with computational analysis while maintaining data quality as requirements change. - Share findings and model performance with technical and cross-functional teams, and support standards for reproducible, high-quality code.

Requirements - PhD in computer science, bioinformatics, computational biology, or a related quantitative field, with emphasis on cancer epigenomics or genomics. - Four or more years of post-PhD experience; the source specifies a range of 4 to 8+ years. - Strong knowledge of high-throughput DNA sequencing analysis, including mapping, alignment, and variant calling. - Experience developing algorithms, applying statistical methods, and building machine learning models such as generalized linear, kernel, tree-based, and neural network methods. - Strong Python and Linux command-line skills, including shell scripting and use of NumPy, Matplotlib, and Pandas. - Ability to communicate scientific findings to technical and non-technical audiences and collaborate across computational and experimental disciplines.

Nice to have - Familiarity with public cancer databases such as TCGA, COSMIC, or OncoKB.

Benefits and work setup - Remote work in the United States. - Listed pay range is $146,000–$182,000 USD; actual compensation varies by experience, skills, and location. - Benefits include medical, dental, vision, life, and disability coverage, fertility care, family leave, retirement benefits, and commuter benefits.