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The Head of Computational Methods Development will lead the strategy, development, and scaling of computational methods that enable extraction of biological and transcriptional signals from epigenomic and liquid biopsy data. This executive leadership role is responsible for establishing and growing a dedicated methods development organization, creating a structured and forward-looking framework that advances platform performance, analytical sensitivity, robustness, and biological insight. Working at the intersection of computational biology, machine learning, and genomics, they will drive the translation of innovative approaches into validated, reproducible methods that support product development, translational research, and clinical applications.
This leader will own the computational methods roadmap, defining technical priorities, guiding execution, and ensuring the delivery of high-quality, production-ready solutions. Key responsibilities include advancing methods for epigenomic signal extraction, noise reduction, normalization, bias correction, and low-input data analysis; developing statistical, probabilistic, and machine learning models; and driving innovation in areas such as deconvolution, representation learning, and longitudinal data modeling. The role will establish rigorous standards for benchmarking, validation, and reproducibility while improving performance in low-signal environments and enabling deeper biological interpretation of complex genomic datasets.
The Head of Computational Methods Development will lead and expand a team of computational biologists, data scientists, and machine learning experts while partnering closely with leaders across computational biology, bioinformatics engineering, translational science, and product development. Success in this role requires deep expertise in computational methods applied to functional genomics or epigenomics, including experience working with noisy next-generation sequencing data and chromatin-based datasets such as ChIP-seq. Candidates should demonstrate a proven track record of translating early-stage scientific concepts into scalable, validated methods and possess the leadership, strategic vision, and operational excellence necessary to build high-performing teams and drive execution within a fast-paced, research-driven organization.
The anticipated annual base salary range for this position is $300,000 to $330,000. This range represents the annual base compensation that the employer reasonably and in good faith expects to pay for the position at the time of posting. Actual compensation will be determined based on factors such as experience, qualifications, skills, and the requirements of the role.