Computational Biology Lead

Mar 30, 2023

Mercy BioAnalytics, Inc. is a biotechnology company committed to reducing suffering and saving lives through the early detection of cancer. We are looking for a passionate individual to join our mission leading Computational Biology for Mercy’s R&D organization.   

This individual will play a critical role in the development of our Mercy Halo blood test portfolio through biomarker discovery and biological interpretation. We are working to solve one of the hardest problems in modern oncology: Can we detect cancer in the blood at its earliest stages, and can we do so in a way that’s accessible to all those that need it? Your responsibilities will include end-to-end support of cancer diagnostic development programs – from identification of biomarker targets, through biomarker screening and into validation studies in large clinical cohorts. You will lead the data analysis, visualization, and interpretation for the company and contribute to our strategy as we develop and commercialize new diagnostic assays.

Candidates for this position must enjoy working for a fast-paced, cutting-edge company and demonstrate exemplary situational leadership capabilities and a passion for contributing to our life-saving mission.


  • Lead target discovery for each iteration of a clinical diagnostic test and continually improve our discovery pipeline with new indication-relevant datasets (CCLE, TCGA, GTEx, CPTAC, etc.) and/or filters derived from previous assay development.
  • Design sample cohorts, author data analysis plans and study reports for internal studies according to QMS guidelines.
  • Develop machine learning models for early cancer detection.
  • Analysis, visualization, and presentation of Mercy Halo data to cross-functional internal and external audiences.
  • Deliver data packages to support publications including conference abstracts, posters, and peer-reviewed manuscripts.
  • Collaborate effectively with data engineering to support the building and testing of infrastructure that supports our lab scientists, clinical sample management, and analysts (i.e. LIMS, data repository, data processing, etc.)
  • Correlate findings from Mercy Halo data with patient clinical records and results from orthogonal studies (RNAseq, IHC, etc) in patient samples to better characterize the Mercy Halo assay.
  • Propose and execute new data QC methods and analytical approaches.
  • Ingest publicly available oncology datasets (genomics, transcriptomics, proteomics) to test novel hypotheses and orthogonally validate internal findings.
  • Model and strengthen our culture of data-based decision making by making data, interpretation and visualization available to scientists across the organization in a timely fashion.


  • PhD in Biological or Computational Sciences with a quantitative biology focus.
  • 5+ years of applying professional competencies to problems in diagnostic, drug development, or industry.
  • Depth in translational oncology with clinical data science experience preferred.
  • Fluency with a high-level programming language such as R or Python for complex data analysis.
  • Demonstrated experience mining and integrating publicly available oncology datasets (genomics, transcriptomics, proteomics, etc.) to identify targets and pathways relevant to early-stage cancer biology.
  • Experience applying computational methods (including statistical modeling and machine learning approaches) to analyze complex human clinical data.
  • Excellent written, oral, and presentation skills; comfortable building data literacy in a small organization.
  • Experience leading and developing a small team.
  • Passion for precision health, and an authentic appreciation for the Mercy mission with a desire to bring a collaborative spirit and strong relationship building, both internally and externally.
  • Ability to work effectively and efficiently in a fast-paced and dynamic innovation-oriented work environment and prioritize among multiple projects and program teams.

Hiring Manager: Chief Scientific Officer

Location: Flexible (on-site, remote or hybrid)

Apply now

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